Reading textual and non-textual explanations in chemistry texts and textbooks – a review

Abstract

Reading is an integral part of chemistry education. The language of chemistry plays a major role when reading chemistry texts and textbooks. Reading textual and non-textual explanations impact students’ understanding of chemistry texts and textbooks. In our review we outline the importance of reading texts and textbooks in chemistry education. We offer different points of view to look at textbook research (conceptual, socio-historical, textual, non-textual) and reading research (readability and comprehensibility) and focus on reading research on textual and non-textual explanations. We point out two major shifts in research interests on texts, textbooks and reading: from readability to comprehensibility and from textual to non-textual explanations. We consider research from the 1950s until today and analyse literature concerning elementary, secondary and tertiary science and chemistry education. Finally, we review ideas for encouraging reading and conclude by presenting recommendations for chemistry education researchers and chemistry teachers on how to improve reading in chemistry education.

---

Language in chemistry education

Language is a crucial element in education. Considering the educational language of every school subject, Cummins (1979) introduced the term communicative academic language proficiency (CALP) for subject-specific language in academic and educational contexts and distanced it from basic colloquial language styles used by students in the early years. Vygotsky (1987) showed that language plays a central role in a person's cognitive development, as developing concepts only works by using language. This means that there is an inextricable link between the development of scientific concepts and language in chemistry education.

Science education research focused on language as a research area and established the term scientific literacy (Norris and Phillips, 2003; Fang, 2005), treating communicative competences as relevant topics in science education. Fang (2005) defines scientific literacy by referring to the interrelationship of both, the fundamental sense of scientific literacy in terms of being able to read and write science texts as well as understanding literacy in its derived sense as being knowledgeable about the contents of science. Fang calls for a development of scientific literacy to maximize learning by using an explicit focus on the specialized language of science (Fang, 2005). Consequently, it appeared that educational programmes set fixed communicative competences to be acquired by students during their school careers (Lee et al., 2013).

Wellington and Osborne (2001) applied integrative language teaching in science more widely. In their book Language and Literacy in Science Education (Wellington and Osborne, 2001), the authors introduce concepts thematising scientific literacy and language activities for science education.

The characteristics of academic language lead to a variety of challenges when teaching and learning in science education (Snow, 2010). As a result, science education research described subject-specific language features and addressed its problems for students’ learning and understanding of scientific concepts (Merzyn, 1987; Taber, 2015; Markic and Childs, 2016).

For example, Johnstone and Selepeng (2001) drew attention to common language misunderstandings in science contexts and increasing problems for students whose second language is English. Seah et al. (2014) show that language in multilingual contexts demands for a shift in science education teaching and research. Similar points for a German-speaking context were made by Sumfleth (1996), who stated that there is a clash between the comprehensibility of chemistry on the one hand and too-demanding academic language requirements on the other. Moreover, Danili and Reid (2006) found that language is one of the factors that plays into students’ test performance. So, language should also be considered when designing assessments in science education (Lee and Orgill, 2022).

Research findings indicate that the understanding of scientific language by students can be improved substantially when language is addressed and supported in science education (Taşdelen and Köseoğlu, 2008; Capanzana and Avilla, 2011; Okanlawon, 2011; Leopold and Leutner, 2012; Dori et al., 2018; Skagen et al., 2018; Finkenstaedt-Quinn et al., 2021). A focus on language can have a positive impact on students’ learning outcomes and understanding of scientific concepts.

For instance, results by Rees et al. (2018) showed that language-focused activities improve the understanding of chemical language. Similarly, Pyburn et al. (2013) point out that the development of language comprehension skills in chemistry education is essential as they found that comprehension skill compensates for deficits in prior knowledge and that there is a correlation between comprehension skills and general chemistry performance.

Chemistry education research has dealt with difficulties in learning the technical language of chemistry more explicitly (Canac and Kermen, 2016; Markic and Childs, 2016; Nyachwaya, 2016) and explored the educational language of chemistry (Scheppegrell, 2001; Taber, 2015). A focus on written texts for descriptive analyses emerged so that chemistry texts and textbooks have often been used to point out characteristic linguistic elements (Thiele and Treagust, 1995; Scheppegrell, 2001; Groves, 2016; Yun and Park, 2018). In the course of time, science and chemistry education research shifted its interests from purely printed and text-based research aims (Cassels and Johnstone, 1985; Meyerson et al., 1991; Carver, 1994) towards a wider understanding of language in science and chemistry education, namely to more non-textual explanations in printed and digital formats (Bergqvist et al., 2013; Liu and Taber, 2016; Enero Upahi and Ramnarain, 2019; Gkitzia et al., 2020; Jian, 2021). These non-textual explanations include all forms of representations that do not solely focus on written words, phrases and sentences but rather add information to texts by including graphs, tables, diagrams, pictures, formulas etc. Here, it was particularly Johnstone's work (1991) on his triangle model that shifted the research interests from textual to non-textual explanations in chemistry texts and textbooks. The fact that chemistry works on three different levels (macroscopic, sub-microscopic and representational) demands for non-textual explanations in texts and textbooks like diagrams, images, symbolic languages and other representations. This shift is important to consider when talking about reading chemistry texts and textbooks, as both, textual and non-textual explanations strongly interact and impact students’ comprehension and learning (Hsu and Yang, 2007; Hung, 2014).

All things considered, language is an integral part of chemistry education. Scientific literacy demands the reading of chemistry texts and textbooks. However, the language of chemistry contains barriers for students’ understanding and learning of scientific concepts. Textual (vocabulary and syntax) and non-textual explanations (representations) in chemistry texts and textbooks impact students’ reading. Chemistry education research has focused on these topics and ensured a research area that is valuable to be reviewed to gain insights into the development of research on reading, texts and textbooks and to encourage students’ reading and learning in chemistry education.

Review aims

We will give an overview of the research areas dealing with reading textual and non-textual explanations in science and chemistry texts and textbooks. We base our review on the following questions:

• Why is reading so relevant in chemistry education?

• What role do chemistry textbooks play as a teaching material for chemistry education?

• How can textbook research in science education be classified?

• How can the readability and comprehensibility of texts be evaluated?

• Which textual explanations frequently occur in chemistry textbooks?

• How do textual explanations interact with non-textual explanations in chemistry textbooks?

• Which strategies exist to encourage reading and students’ comprehensibility and how effective are they?

• Which recommendations can be found for chemistry education researchers and chemistry teachers to encourage reading in their education?

To address the research questions we follow a narrative approach. By taking into account the role of reading, textbook research and the language of chemistry texts and textbooks, we seek to synthesize qualitative findings from readability and comprehensibility research.

We include literature that deals with at least one of the following topics: reading, science/chemistry texts, science/chemistry textbooks, readability, comprehensibility, vocabulary, syntax, representations, methods and strategies for encouraging reading. We base our review on both aspects of language in chemistry texts and textbooks, namely textual and non-textual explanations.

For our review, we did not exclude specific databases or information sources in order to give an extensive overview of the research field and to do justice to the fact that research on text and reading developed in an interdisciplinary field. This means that we do not solely focus on chemistry texts and textbooks but will also include findings from general reading research. Some findings that we will discuss relate to science texts in general or do not consider the classical chemistry textbooks but will otherwise focus on language features and representations or include other curriculum material.

Moreover, we do not specify on literature concerning a specific time frame so that our review includes literature from the 1950s until today. We include research about elementary, secondary and tertiary education to cover a wide range of research findings and to take into account that reading is substantial for chemistry researchers’ work (Shanahan and Shanahan, 2008). We are also aware that no consistent picture can be drawn from our language-focused review as many studies included come from all over the world. The variety of analysed languages and student groups does not allow to draw any consistent conclusions about the entire reading research on textual and non-textual explanations but allows to create a general overview of approaches and methods of the research field.

We begin by outlining the role of reading and textbooks in chemistry education and proceed with introducing main science textbook research areas (conceptual, socio-historical, textual, non-textual) and reading research areas (readability and comprehensibility). In our review we focus on the language aspects of chemistry texts and textbooks and give an overview of research on textual and non-textual explanations in chemistry texts and textbooks. We point out two major shifts in research interests on texts, textbooks and reading: from readability to comprehensibility and from textual to non-textual. Finally, we review literature about ideas for encouraging reading in chemistry education and conclude by giving recommendations for chemistry education researchers and chemistry teachers on how to improve reading texts and textbooks in chemistry education.

The role of reading in chemistry

Reading plays an important role in education (Sumfleth, 1996; Snow, 2010; Wright et al., 2016). It is one of the major methods for learning and a way to acquire new knowledge and simultaneously linguistic competence from textual and non-textual elements (Nigro and Trivelato, 2012). Reading is an integral part of scientific literacy and impacts the teaching of disciplinary literacy in chemistry education (Shanahan and Shanahan, 2008).

Reading plays an essential role in chemistry-related occupations and particularly in chemistry research. Chemists need to read experimental test protocols before conducting experiments and have to read other researchers’ scientific articles to base their own research on other researchers’ work. By analysing expert readers, Shanahan et al. (2011) described how researchers are reading texts. They found that there are considerable differences among different expert readers of different disciplines. Especially, expert readers of chemistry research strongly rely on re-reading texts and use non-textual explanations like graphics to comprehend chemistry texts (Shanahan et al., 2011).

With reference to chemistry education, research shows that reading ability correlates with general chemistry performance (Cano et al., 2014; Korpershoek et al., 2015; Stoffelsma and Spooren, 2019). Korpershoek et al. (2015) found that both, mathematics and reading ability, are positively related to secondary school students’ mathematics, physics and chemistry examination grades. Neither sex nor students’ ethnicity were predictors of better or worse results (Korpershoek et al., 2015). They showed that academic achievement is strongly influenced by secondary school students’ reading proficiency (Korpershoek et al., 2015). Similar findings for first-year science and mathematics university students in a non-Western multilingual academic context support the role reading plays in education (Stoffelsma and Spooren, 2019).

Moreover, reading comprehension is positively related to secondary students’ question-asking and knowledge-building and general academic achievement in science (Cano et al., 2014). Students’ scientific inquiry performance of forming researchable questions and planning experimental procedures could effectively be enriched by reading (Tseng et al., 2022).

Reading also impacts other language issues in chemistry education, like writing. So, Deng et al. (2019) showed that scientific writing of undergraduate students regarding experiments in organic chemistry can successfully be improved by reading tasks.

To sum up, we see that reading plays an important role in chemistry occupations and chemistry education. Encouraging students reading has positive effects on their chemistry performance and scientific language skills. But what role do chemistry texts and textbooks actually play in chemistry education and how do teachers respond to the role reading plays in chemistry education?

The role of chemistry textbooks in chemistry education

Chemistry teachers rely on textbooks since these provide the teaching content and its sequence (Chen and Wei, 2015). Chemistry textbooks are a frequently used curriculum material for teachers’ lesson preparation or to check the latest curriculum standards (Chen and Wei, 2015). However, Chen and Wei (2015) showed that chemistry teachers in China consciously adapted chemistry textbooks for their own teaching procedures since textbooks often fail to include activities that can be used in chemistry classrooms and fit to students’ demands.

It is the teachers’ job to investigate existing chemistry textbooks and to choose an appropriate textbook to use in the chemistry classroom (Vojíř and Rusek, 2021). In terms of reading, teacher-focused studies showed that chemistry teachers consider chemistry textbooks a less favoured teaching material (O'Brien and Stewart, 1990; Yore, 1991; Beerenwinkel and Gräsel, 2005; Seah, 2016).

Yore (1991) investigated chemistry teachers’ attitudes towards and beliefs of reading textbooks in chemistry education. There seems to be a clash between the important role that chemistry teachers attribute to reading in chemistry and their way of teaching and handling reading in chemistry education (Yore, 1991). According to Yore (1991), science teachers reject a text-driven model of reading and acknowledge that technical vocabulary in science texts plays an important role in students’ difficulties in comprehending science texts (Yore, 1991).

These findings appear to be in line with a study by Beerenwinkel and Gräsel (2005). A survey of more than 200 chemistry teachers in Germany showed that chemistry textbooks are rarely used in chemistry education. When they are used, it is mainly for students’ home assignments (Beerenwinkel and Gräsel, 2005) rather than for reading phases. Chemistry teachers appear to be very dissatisfied with chemistry textbooks. The distance of texts to students’ interests and the language used are major reasons for chemistry teachers to use chemistry textbooks sparsely (Beerenwinkel and Gräsel, 2005).

Also pre-service chemistry teachers criticise traditional chemistry textbooks. In a study by Taşdelen and Köseoğlu (2008), learner-friendly narrative texts about acids and bases were used instead of traditional textbooks to investigate how pre-service teachers react to these new texts. Understandability was a major criterion for pre-service chemistry teachers to evaluate chemistry texts. The absence of typical textbook language, and the alternative to the standard structural composition of textbooks, were major reasons for pre-service chemistry teachers to choose the narrative texts over traditional textbook passages (Taşdelen and Köseoğlu, 2008).

All in all, studies about the use of textbooks by chemistry teachers show that teachers are aware of advantages and difficulties of chemistry textbooks. There is one point that always arises in teachers’ complaints, namely the language requirements that traditional chemistry texts and textbooks demand from students. Science education research has acknowledged the role of reading and textbooks in science education and ensured different textbook research areas.

Science textbook research areas

Science education research covers several distinct areas of textbook research. A systematic literature review about science education textbook research by Vojíř and Rusek (2019) gives an overview about research areas concerning textbooks. Their analysis of 183 papers (published from 2000 to 2018) provided 13 distinct topics of research interests in textbook research (Vojíř and Rusek, 2019). Among others, content, learning concepts and non-textual explanations are the most dominating topic groups of textbook research articles in science education (Vojíř and Rusek, 2019). In the course of time, articles dealing with non-textual explanations in textbooks has grown while only 6% of the analysed papers were categorized by the authors as dealing with purely textual issues (Vojíř and Rusek, 2019).

We will now briefly present different research areas of science education on textbooks to extract two that refer to our focus on language.

First, content-related research approaches focus on the analysis and evaluation of content, concepts and students’ learning (Vojíř and Rusek, 2019). For instance, articles in this research area explored how far and to what extent chemistry textbooks fail to include content about electrolysis (Chang et al., 2020) or how chemistry textbooks impact on students’ conceptional confusion about acids and bases (Lembens et al., 2019).

Second, publications in science textbook research have focussed on gender-related and ethnicity-related issues. Debates in society (e.g. social problems regarding gender and ethnicity equity) are being applied to science textbook research. For instance, findings show that chemistry textbooks fail to depict gender representation (Becker and Nilsson, 2021). Similarly, textbook research about historical developments of textbooks and curriculum reforms and their impact on textbooks can be grouped here as they also deal with textbook content on a meta-level (Vojíř and Rusek, 2019).

Third, text-related questions appear to be of less interest in textbook research in science education (Vojíř and Rusek, 2019). Although language plays a crucial role in chemistry education and reading chemistry text and textbooks impacts students’ learning of scientific concepts, less research exist in the field of textual explanations in science texts and textbooks. In our review we hold on to show general findings from reading and textbook research to maintain a text-related approach to chemistry textbook research and outline research gaps to consider in future chemistry education research on texts and textbooks.

Finally, non-textual explanations in science texts and textbooks (e.g. graphics, visuals, mechanistic language features etc.) are frequently described, categorized and evaluated in terms of comprehensibility and learning (Bhattacharyya, 2014; Enero Upahi and Ramnarain, 2019; Atkinson et al., 2021; Connor et al., 2021; Jian, 2021). The language of chemistry encompasses not only textual explanations but also non-textual explanations. Both aspects of language in chemistry texts and textbooks interact and impact students’ reading of chemistry texts and textbooks so that an integrated model of textual and non-textual comprehensibility can frequently be found in empirical studies on texts and textbooks, for example in Bergqvist et al. (2013). In our review, we focus on the reading of both, textual and non-textual explanations in chemistry texts and textbooks. To analyse and evaluate the impact these explanations have on students’ reading, reading research has developed two major research directions, namely readability and comprehensibility research.

Readability and comprehensibility research

There are two ways of investigating the effects that textual and non-textual explanations have on readers’ understanding, namely readability and comprehensibility. Both approaches differ significantly in their methods and goals. In the course of time, there was a shift from readability to comprehensibility research as the focus changed from purely text-centred to reader-centred approaches in reading research.

Readability research

Readability research relies on a strong focus on the text itself and does not necessarily examine the interaction between the texts and their readers (Nunan, 1991; McCarthy, 1999; Bailin and Grafstein, 2016). Through analysing linguistic surface features of texts, readability studies hypothesize that the linguistic make-up of texts makes texts easier or harder to read (McCarthy, 1999; Bailin and Grafstein, 2016). Variables to scan for in readability research are therefore the length of a text, number of clauses, length of clauses, number of difficult words, etc. Readability research sets a correlation between reading rate and evaluations of the difficulty of texts by experts, and finally compiles readability formulas such as the Flesch formula, the FOG TEST, the FRY readability graph or the SMOG formula to evaluate the readability (Kennedy, 1979; Bailin and Grafstein, 2016; Beier et al., 2021).

The interaction between text and reader is absent in readability research, meaning that the comprehensibility of texts under realistic circumstances can only be implicitly evaluated.

Exemplary studies for readability research are the studies by Mallinson et al. (1952) and Chiang-Soong and Yager (1993) who evaluated the difficulty of texts by only considering the texts and their linguistic characteristics. Using the Flesch formula, they found that in the 1990s, most chemistry textbooks were too demanding for students’ age groups regarding the readability of texts (Chiang-Soong and Yager, 1993).

In reading research, it remains unclear as to what extent the measuring of the readability of texts pays off when actual students are confronted with texts.

Nowadays, readability studies are absent from most research projects. However, sometimes research uses readability formulas for methodological designs of studies on the comprehensibility of texts (Rapp, 2001; Udu et al., 2016).

Comprehensibility research

In contrast to readability research, comprehensibility research consciously considers the interaction between the reader and the text. In this research framework, reading is understood to be a continuous interplay between two simultaneous processes, the top-down process and the bottom-up process (Rumelhart, 1977; Dubin and Bycina, 1991; Bintang Nadea et al., 2021).

The top-down process refers to the way the readers check the coherence of their ideas on the text and adjust them if necessary (Dambacher, 2010). The bottom-up process is guided by the text itself and happens when readers construct ideas from the text and their prior knowledge (Dambacher, 2010). This model emphasises the role readers play when working with a text so that the cognitive comprehensibility processes of recipients are incorporated in comprehensibility research.

Every reader of a text reads by constructing and solving problems (Rumelhart, 1977; Sumfleth, 1995). The text-driven bottom-up process is as important when measuring the comprehensibility of texts as are the cognitive features, targets and interests of the readers themselves (Schraw and Dennison, 1994; Neiles, 2012; Ho et al., 2014). Readers’ linking of information and their own mental structures lead to an in-depth processing of the content, so that the reader is able to construct and re-construct textual and non-textual information (Kintsch and van Dijk, 1978; D'Mello and Mills, 2021).

In contrast to readability formulas, whose variables and factors are mainly determined by features inherent to a text, the cloze procedure test measures the comprehensibility of texts by considering the interaction between the text and the reader (Bormuth, 1968; Fatoba, 2014). The cloze technique involves a text in which words are omitted, which must then be filled in by students. This enables researchers and teachers to find out how difficult the texts are for their readers. Researchers still use the cloze technique to investigate the comprehensibility of texts in student groups (Fatoba, 2014; Bansiong, 2019).

Reader-centred research questions in comprehensibility research deal with individual differences among students and factors such as students’ interests in the topic, students’ pre-existing knowledge or additional instructions and strategies (Schraw and Dennison, 1994; Taboada and Guthrie, 2006; Neiles, 2012; Ho et al., 2014; Jian, 2019).

For instance, Neiles (2012) analysed the effects of reader characteristics on reading comprehension of a general chemistry text and found that students’ prior knowledge is a strong predictor of better comprehensibility scores. Additionally, working memory and fluency practice (Budd et al., 1995; Savage et al., 2007; Swanson and O'Connor, 2009) and metacognitive prompts and reading strategies (Leopold and Leutner, 2012; Wang et al., 2014; Dori et al., 2018; Yen et al., 2018; Lennox et al., 2020) have the potential to positively impact students’ comprehensibility of texts. Moreover, the work by Jian (2019) shows that reading instructions can positively influence integrated textual and pictorial reading (Jian, 2022).

Both approaches of reading research, readability and comprehensibility research, focus on language aspects of reading. While readability research mainly relies on text-inherent features and their impact on the difficulty of texts, comprehensibility research analyses and evaluates the impact of changes in both, the texts and the readers, on the comprehensibility of texts. For reading chemistry texts and textbooks, textual and non-textual explanations impact the readability of texts and students’ comprehensibility so that a closer look at these explanations is necessary to find out more about ways for encouraging reading in chemistry education.

Textual and non-textual explanations in chemistry texts and textbooks

We will now explore textual and non-textual explanations in chemistry texts and textbooks by presenting findings from readability and comprehensibility research. We will show that there is a shift in chemistry education research interests from purely textual analyses of chemistry texts (vocabulary and syntax) to more non-textual analyses (representations).

To start with, the connection between language and scientific learning and the important role of scientific literacy led to several studies describing typical linguistic features of the educational language in science (Scheppegrell, 2001; Wellington and Osborne, 2001; Seah et al., 2014; Markic and Childs, 2016; To and Mahboob, 2019). Some linguistic features are widely agreed on as being characteristic for educational texts and language in textbooks as academic communication strives to be precise, economical, objective, differentiated and anonymous and demands for specific linguistic features to achieve this (Scheppegrell, 2001).

While linguistic analyses and evaluations of chemistry textbooks have been carried out for a long time (Mallinson et al., 1952; Kennedy, 1979; Yager, 1983; Chiang-Soong and Yager, 1993; Groves, 1995; Sumfleth, 1995), school-based science language was first considered towards the beginning of the 21st century (Scheppegrell, 2001) and usually occurs on three levels: the morphological level, which takes into account vocabulary and its features, syntactic characteristics of texts and structural descriptions including the organisation of texts and representations like diagrams, images, formulas etc. (Scheppegrell, 2001; Härtig et al., 2015). In our review we group vocabulary and syntax, as part of the micro-level of texts, to textual explanations and the organisation of texts and representations, as elements on the macro-level, to non-textual explanations in chemistry texts and textbooks.

Textual explanations

The language of chemistry is full of unknown and complex words. Technical terms, in particular compound words (e.g. hydrogen bridge bond), nominalizations (e.g. the verb “to mix” becomes “the mixing”), abbreviations (e.g. DNA for deoxyribonucleic acid) and acronyms (e.g. LUMO – Lowest Unoccupied Molecular Orbital) are widely agreed linguistic features of chemistry texts and textbooks (Marshall et al., 1991; Scheppegrell, 2001; Wellington and Osborne, 2001; Fang et al., 2006; Taber, 2015; Markic and Childs, 2016).

The focus on science vocabulary has a long history in science education research. Cassels and Johnstone's book Words That Matter in Science(1985) shows that science vocabulary does not only encompass technical language (words such as oxidation, electrolysis, etc.) but also ‘general’ English words that are frequently used in science contexts and that can easily lead to students’ incomprehensibility of science content (e.g. constituent or tabulate).

A way of grouping the extensive science vocabulary was introduced by Wellington and Osborne (2001). They developed a system by classifying words into three categories: scientific words (e.g. cathode, ion), semi-technical words (e.g. particle, material) and non-technical words that are widely used in science (e.g. adjacent, volume). Their classification system further classifies scientific words as being either unique to science (e.g. atom) or having additional everyday meanings (e.g. charge). Similarly, semi-technical words can have one meaning only (e.g. flow) or dual meanings (e.g. positive). The same is true for the final category of non-technical vocabulary with one meaning (e.g. minimum) or dual meanings (e.g. effect) (Wellington and Osborne, 2001).

Scientific language uses many synonyms, so that many words in chemistry have at least one other word with almost the same meaning (e.g. covalent bond and atomic bond) (Taber, 2015). It is also important to keep in mind that words in science have different meanings among the three sciences themselves (e.g. a field in physics and a field for planting in biology) or among sub-disciplines of a single science (e.g. condensation in physical and in organic chemistry) (Fitzgerald et al., 2017).

Research on vocabulary shows that the great spectrum of vocabulary and its intersections with students’ everyday language makes the learning of chemical concepts quite demanding for students.

To start with, several studies address vocabulary loads and their density to explain the readability and comprehensibility of texts (Cassels and Johnstone, 1985; Carver, 1994; Groves, 1995; Biber et al., 2004; Groves, 2016; Yun and Park, 2018).

For example, when analysing the vocabulary loads of chemistry textbooks over time, Groves (1995, 2016) found that the vocabulary load in analysed chemistry textbooks decreased from almost 3000 terms in a chemistry textbook from the 1980s to almost half that in a textbook from 2012 (Groves, 2016). Earlier findings showed that the vocabulary loads per year in science textbooks are as close to the vocabulary loads per year in secondary language teaching (Yager, 1983; Groves, 1995).

It was found that the amount and density of unknown and complex vocabulary in science texts can negatively impact the readability of texts (Carver, 1994) and can become particularly demanding for non-native speakers (Childs and O'Farrell, 2003).

Many studies on students’ understanding of science vocabulary showed that too many students had problems with understanding and correctly using science vocabulary (Pickersgill and Lock, 1991; Carver, 1994; Childs and O'Farrell, 2003; Song and Carheden, 2014; Cervetti et al., 2015; Fitzgerald et al., 2017; Hiebert et al., 2019).

Song and Carheden (2014) analysed dual meaning vocabulary (DMV) and its perception and comprehensibility by chemistry students. Their findings indicated that many college students associated personal experiences from everyday life when dealing with dual meaning vocabulary (DMV), which meant that they had trouble with retaining the scientific meaning behind these words (Song and Carheden, 2014).

When looking at the words themselves more closely, Hiebert et al. (2019) found that word length, number of syllables, concreteness and word location affect students’ understanding and performance in education.

Yun (2021) showed, by using eye-tracking tests, that students with low-level comprehension engaged less in repeated learning and focused less on specialised vocabulary while high-level students spent more time on reading unfamiliar words.

Arya et al. (2011) analysed third-grade students’ understanding of different forms of linguistic make-ups of texts. They took external factors of reading achievement and prior knowledge of vocabulary into consideration. The necessity of syntactically simple texts cannot be verified by the authors (Arya et al., 2011). However, lexical complexity (in terms of word frequency and word knowledge) significantly impacts students’ comprehension (Arya et al., 2011). In addition, English language learners (ELLs) showed no significant differences in comprehension tests after reading syntactically and lexically altered texts when compared to native speakers of English (Arya et al., 2011).

However, the results could not be confirmed by Härtig et al. (2019) for German chemistry and physics texts. They found that after altering the morphological level (using everyday language, using less scientific terms and explaining DMV), comprehension test results were not significantly higher (Härtig et al., 2019). Instead, ninth-grade students’ pre-existing knowledge was a dominant predictor of higher understandability scores (Härtig et al., 2019). The findings were positively interpreted by the authors as they claimed that students’ linguistic performance is good enough to understand complex science texts (Härtig et al., 2019).

We can conclude that much research focuses on the vocabulary of chemistry texts and textbooks. Beginning with classifying words and their features, to measuring vocabulary amounts in chemistry textbooks up to references to difficulty factors of scientific words, science education research has always focused on specialised terms and various aspects of chemistry vocabulary to find out more about students’ difficulties and encourage students’ reading and comprehensibility of texts.

It appears to be true that students have difficulties with particular vocabulary features. However, not all studies can show evidence of how morphological changes on the textual level of science texts can positively affect students’ comprehensibility and learning (Härtig et al., 2019). Here, more studies are necessary to find out about students’ difficulties and, more importantly, about how to effectively deal with these difficulties in chemistry texts and textbooks.

In contrast to science vocabulary which has often been of interest to educational research, syntactic features of scientific language have gained less attention in science education research. However, fixed syntactic structures are frequently used when writing textbooks and syntactic characteristics of academic register have been of focus in linguistics (Biber and Gray, 2010; Conrad, 2019; Gray, 2021).

Subordinate clauses, passive voice and complex noun phrases are characteristics of academic writing, educational texts and language in chemistry textbooks (Merzyn, 1987; Halliday, 1989; Scheppegrell, 2001; Wellington and Osborne, 2001; Snow, 2010; Bryce, 2013; Muspratt and Freebody, 2013; Härtig et al., 2015; Biber, 2019).

Chemistry texts contain many subordinate clauses that express a conditional or causal meaning (Scheppegrell, 2001). This syntactic structure is typical for scientific, but rather unusual for everyday language (Snow, 2010) as many information are linked to each other in chemistry texts (e.g. in order to express causal relations of chemical processes). Many students encounter this structure only in educational contexts and have difficulties understanding these complex linguistic features when reading a chemistry text (Scheppegrell, 2001).

Additionally, polysemy is not only a problem at the morphological level of educational language, but syntactic structures are polysemous too. The passive voice, for instance, is typically used to describe actions and processes where there is no consciously acting agent (Kniffka and Roelcke, 2016). Passive voice can be found in chemistry texts as they often describe processes rather than actions (e.g. water is added) (Scheppegrell, 2001). Passive voice is also quite frequent when writing about the sub-microscopic level in chemistry as particles usually do not consciously react but are bonded etc. so that no agent is present (e.g. electrons are transferred) and passive voice is used to describe these processes.

Due to the necessity to encode and link complex information in a very precise way, highly complex syntactic structures are typical for educational and academic language in chemistry texts and textbooks (Scheppegrell, 2001; Biber and Gray, 2010; Arya et al., 2011; Bryce, 2013; Kniffka and Roelcke, 2016; Biber, 2019). The increased use of complex sentences and strategies of dense information being packed in phrases and sentences on the other is typical for chemistry textbooks (Kniffka and Roelcke, 2016). It manifests in the frequent use of complex noun phrases – a characteristic feature of academic and educational language (Scheppegrell, 2001; Fang et al., 2006; Biber and Gray, 2021). They allow dense information being packed in a clause (e.g. during the cooling-down, the change of physical state happens at the same temperatures as during the heating-up). The longer the single constituents, the more important well-developed reading skills are, including a certain speed in decoding (Savage et al., 2007; Swanson and O'Connor, 2009). If students struggle with decoding single words or have a weak working memory, it is likely that they cannot keep the single words in their working memory long enough to parse and comprehend a long phrase or sentence (Savage et al., 2007; Swanson and O'Connor, 2009; Ariasi and Mason, 2014).

As said before, there is little evidence in science education textbook research about syntactic structures and especially about the impact of syntactically simplified texts. The studies by Arya et al. (2011) and Härtig et al. (2019) show no positive effects of syntactically altered texts on students’ understanding and learning from science texts. Although working memory theory and linguistics indicates that syntactic complexity of texts influences students’ comprehension performance, no evidence can be found in science education research on textual explanation in chemistry texts and textbooks.

To sum up, we see that scientific language in education demands for complex textual explanations on the morphological and syntactic level. Vocabulary in chemistry encompasses a wide range of words from science and everyday language. Chemistry vocabulary is dense in science texts and textbooks which mirrors in highly complex syntactic structures. While studies on the morphological level can be found in both research directions, readability and comprehensibility research, studies on the syntactic level of chemistry texts and textbooks are almost absent from science education textbooks research. For textual explanations, more research is necessary. The morphological and syntactic level of chemistry texts only work together so that renewed research designs can be a starting point to evaluate the effects of morphologically and syntactically altered texts on students’ understanding.

Non-textual explanations

Texts in chemistry textbooks are not only compiled by written text paragraphs with particular argumentation strategies and text cohesion criteria. There are images, diagrams, formulae, mechanistic language features and spectra that significantly influence the reading of a text. Taken together they belong to non-textual explanations. Although the organisation of a text is created by textual features like connectors etc. we group these characteristics here as they work similarly on the macro level of texts as representations. Research on non-textual explanations has shown positive effects on students’ comprehensibility when reading scientific texts.

To begin with, the organisation of a text, like paragraphing and cohesion are specific for chemistry texts and textbooks. There are many connectors in chemistry texts to generate coherent contents and allow to explicitly communicate scientific concepts and ideas. These structural features on the textual level of science texts impact students’ reading. Sumfleth (1995) showed that linguistic text comprehensibility criteria help to increase reading comprehension. The authors show that the cognitive structuring of a text and semantic redundancy are among the parameters that most significantly impact the comprehensibility of texts (Sumfleth, 1995).

The organisation of a text also encompasses non-textual explanations in terms of representations. Vojíř and Rusek (2019) showed that more and more textbook research exist in terms of non-textual explanations of science texts. Representations like images, formulae etc. and their interaction with textual explanations in chemistry texts and textbooks impact students’ reading. Reading in chemistry education involves both, the reading of textual and non-textual explanations so that scientific literacy does not only refer to students’ understanding and argumentation competence when dealing with verbal scientific language features (Fang, 2005) but does also include representational competence (Kozma and Russell, 2005).

Representational competence refers to “a set of skills and practices that allow a person to reflectively use a variety of representations or visualizations, singly and together, to think about, communicate, and act on chemical phenomena in terms of underlying, aperceptual physical entities and processes” (Kozma and Russell, 2005, p. 131). Representational competence has frequently been of interest in chemistry education research (Atkinson et al., 2021; Parobek et al., 2021; Popova and Jones, 2021; Tóthová et al., 2021; Watts et al., 2022) and has been considered when evaluating the effect of representations on students’ learning (Larkin and Simon, 1987; Hsu and Yang, 2007; Ariasi and Mason, 2014; Enero Upahi and Ramnarain, 2019; Gkitzia et al., 2020).

Johnstone's work on the triangle model of chemistry education (Johnstone, 1991) had significant impact on chemistry education research on representations. Johnstone outlined three major levels of chemistry (Johnstone, 1991). First, the macro-level is very descriptive and functional as it refers to things that we can see and handle and which properties we can easily describe. Second, the sub-micro level refers to the molecular level and serves for explanations of the macro-level. Here, chemists tend to explain why chemical substances behave the way they do and how and why they react. Third, the symbolic level tries to represent chemical substances and particles by formulae and their change of equations. Taken together, all three levels of chemistry demand for representations (e.g. images of the substances, formulae for equations and pictorial representations for particles). To move between the various levels of understanding (macroscopic, sub-microscopic and symbolic) calls for much working memory capacity for students when learning chemistry (Reid, 2021) and impacts students’ comprehensibility when reading chemistry texts and textbooks.

There was a renunciation of textbook research in science education about textual features toward a wider and holistic approach of textbook research by integrating non-textual features like representations. We turn now to several studies that analysed the effect of representations on students’ learning and reading.

To start with, when a text about sodium chloride was given to a sample of more than 60 female ninth-grade students in Oman, students’ mind-wandering and reading comprehension was measured (Al-Balushi and Al-Harthy, 2015). The authors found that students’ mind-wandering was significantly higher when reading sub-microscopic textual narrations than when reading on the macroscopic level (Al-Balushi and Al-Harthy, 2015). Additionally, a significant negative correlation was revealed between comprehension test results and students’ mind-wandering for both levels of representation (Al-Balushi and Al-Harthy, 2015).

When comparing two versions of a text, one designed traditionally and the other varying in its extent of representational structures and their interactions, Hsu and Yang (2007) found that Taiwanese junior high school students’ performance after reading the re-designed text was significantly higher than after reading the traditional text. Additionally, students’ misconceptions were significantly higher after the reading of the traditional text (Hsu and Yang, 2007). Equally, Hung (2014) measured students’ eye-movement behaviours and showed that print received more attention by Taiwanese grade 6 readers than illustrations. However, having more fixations on illustrations led to higher comprehensibility by students (Hung, 2014).

Ryoo et al. (2018) analysed eight grade students’ short-term and long-term understanding of chemical phenomena using visualizations and found significant improvement in students’ understanding. Additionally, they showed that both English language learners (ELLs) and non-ELLs benefit from the use of interactive visualizations, implying that all students should read textual and non-textual explanations in chemistry.

To find out more about the delayed effects of text-diagram reading on reading comprehension and learning, evidence from eye movements show that fourth-grade students who receive text-diagram reading instruction before reading spent significantly more reading time on images and diagrams and make more integrative transitions between both (Jian, 2021). These results appear to be more evident for immediate effects than for delayed effects (Jian, 2021) so that it remains open in how far text-diagram reading can be supported by educators on a long-term basis.

Continuing with eye-movement studies, it was found that picture labelling affects science text processing and learning (Mason et al., 2013). For effective reading of both, textual and non-textual explanations it is necessary to implement direct references between both of them in order to consider the text-diagram reading strategies of Mayer's cognitive theory of multimedia learning (Mayer, 2014).

Gender differences in eye movements while solving text-diagram reading problems were analysed by Huang and Chen (2016). They found that female junior high school students spent more time to read the print texts and compare them with the information given in visual-based diagrams (Huang and Chen, 2016). The authors conclude that it is desirable that instructions for explicit text-diagram reading are given to students and that more time should be spent in science education to teach strategies for improving science learning by using textual and non-textual reading (Huang and Chen, 2016).

For chemistry, education research also focuses on specialised forms of representations like symbolic language features of the language of chemistry (Taber, 2015; Liu and Taber, 2016) or mechanistic language features in organic chemistry (Bongers et al., 2019; Watts et al., 2022). Research by Bhattacharyya (2014), Galloway et al. (2017) and Graulich and Caspari (2021) outline differences of students’ reading and interpretation of mechanistic language in chemistry and spectra are evaluated in terms of reading texts on the tertiary level (Topczewski et al., 2017; Connor et al., 2021).

To sum up, we see that science education research shed light on the organisation of texts and non-textual explanations of science texts that play into students’ interpretation and understanding of chemical concepts when reading. Research of the 21st century does mainly rely on eye-tracking methodology in order to find out more about students’ comprehensibility processes when reading textbooks (Mason et al., 2013; Ariasi and Mason, 2014; Ho et al., 2014; Topczewski et al., 2017; Jian, 2019, 2021). Reading instructions addressing representations in scientific texts and promoting text-diagram reading in science education are effective strategies to support students’ learning when reading science texts and textbooks. The three levels of chemistry (macroscopic, sub-microscopic and symbolic) demand for representations that support students’ understanding while reading chemistry texts and textbooks. Studies dealing with effects of integrated textual and non-textual reading demonstrate that chemistry teachers can enhance students’ reading when focusing on both, textual and non-textual explanations, equally. The shift from textual to non-textual research interests provided evidence that demonstrates the importance of an integrated reading model including both, textual and non-textual elements in chemistry texts and textbooks. This should also be considered when discussing ways and methods for encouraging reading in chemistry education.

Encouraging reading in chemistry education

Knowing about the difficulty of textual and non-textual explanations in chemistry texts and textbooks is relevant for chemistry educators to encourage reading in chemistry education. The German physicist and educational researcher, Josef Leisen (2020), points out two ways of using texts. First, by changing text inherent features (defensive method) and second by changing the reader and its interaction with the text (offensive method) (see Fig. 1).

Fig. 1 Science textbook research on textual and non-textual explanations.

The offensive method tries to adapt the reader to the features of a text so that strategies, students’ prior knowledge and reading tasks are used to support the reading process and students’ comprehension of what they read (Leisen, 2020). Second, adapting texts to students’ knowledge and language is represented as a defensive way of dealing with the reading of texts (Leisen, 2020) and should be used sparsely because the reader is to be given the competence to comprehend texts in the long term only when he is confronted with demanding texts. The adaption of the reader to the text is the most urgent task to build up and develop reading competence and to enable students to autonomously deal with highly complex academic texts beyond science education (Leisen, 2020). While defensive methods encompass simplifications of textual and non-textual explanations or using alternative texts and teaching material, offensive methods include reading strategies.

Defensive methods

Findings from both, readability and comprehensibility research, show that simplifications of texts can be used to improve students’ reading and understanding. Difficulties of textual and non-textual explanations like dual meaning vocabulary, complex noun phrases or representations should be addressed by teachers when designing simplified chemistry texts or choosing chemistry textbooks. However, for many alternations on the textual level it remains unclear if and what kind of morphological and syntactic changes have the potential to significantly support students’ understanding (Härtig et al., 2015).

Another defensive method is to substitute traditional chemistry texts and textbooks by alternatives. Ideas for using textbooks in non-traditional formats were put forward in order to meet the demands of the 21st century (Robinson et al., 2014; Allen et al., 2015). Digitalisation has developed new ways of using texts and textbooks in chemistry education. There are many studies on replacements of traditional printed textbooks and their effects on students’ learning (Robinson et al., 2014; Allen et al., 2015; McCollum, 2016; Moundy et al., 2021; Sansom et al., 2021). Printed textbooks have been pushed into the background while digital formats and open-educational resources replaced the traditional printed textbooks.

Quantitative empirical findings show small but positive effects of open textbooks (Robinson et al., 2014) and postulate OERs as useful material resources for teachers that can significantly stimulate reading in chemistry education (Robinson et al., 2014). Open educational resources such as ChemWiki, evaluated in a study by Allen et al. (2015), are a favoured source of teaching material for educators. ChemWiki was re-developed and became LibreText, an open online textbook platform (Larsen et al., 2017). Students’ performance in general chemistry classes after reading ChemWiki was not inferior to the performance of students who used traditional textbooks (Allen et al., 2015) so that open educational resources do not make a difference to the outcomes of students’ performance and are viable cost-saving alternatives to traditional textbooks (Allen et al., 2015).

Equally, Sansom et al. (2021) let first-year undergraduate students choose whether to use traditional and most often quite expensive textbooks or to use open-educational resources. They found that both, students using the OERs and the commercial textbook, performed on a similar level in general chemistry (Sansom et al., 2021) so that OERs might work as no-cost materials that instructors can use to provide quality information to students.

Another study by Dağlı Gökbulut and Güneyli (2019) showed that the vocabulary acquisition levels of special needs students were better when reading texts presented through electronic books in a computer environment than reading regular printed texts. Moreover, electronic texts were found to be more effective than printed texts in improving the reading comprehension skills of special need students (Dağlı Gökbulut and Güneyli, 2019).

Besides digital textbooks and open-educational resources, other alternative texts can be used in science education. For example, Phillips and Norris (2009) demontrated that adapted primary literature serves as a successful instruction innovation for science education, as it tries to fill the gap between the complex language of science and the simplified language of school science. So, instead of taking too-demanding school textbooks as a starting point, the authors tried to explore the extent to which realistic scientific language can be part of chemistry education when dealing with authentic reading material (Phillips and Norris, 2009).

Defensive methods for encouraging the reading of chemistry texts and textbooks do either simplify the textual and non-textual explanations of chemistry texts and textbooks or replace traditional printed textbooks by digital formats, open-educational resources or adapted primary literature. Defensive methods show positive effects on students’ reading and learning but do not allow students to enhance their language skills of chemistry as reader characteristics that impact the reading of textual and non-textual explanations are absent. In contrast to defensive methods, offensive methods take into account readers’ impact on reading.

Offensive methods

In addition to replacing textbooks and using new educational resources, science education research has pointed out some ways of how to adapt readers to texts to effectively increase students’ comprehensibility while reading.

Reading strategies allow chemistry educators to adapt students to chemistry texts and textbooks. They enhance students’ autonomous confrontation with textual and non-textual explanations and enable students to deal with highly complex academic texts beyond science education. For example, switching between different forms of representation can be an effective strategy that leads to higher comprehension scores by students. Leopold and Leutner (2012) showed that drawing strategy instructions significantly affects higher reading outcomes by tenth-grade students. Similar results exist for the effectiveness of reading strategies such as predicting and summarizing (Leopold and Leutner, 2012). The reciprocal teaching approach by Capanzana and Avilla (2011), which provides nine graders with strategies like predicting, question generating, clarifying and summarizing, proved to successfully assist students’ reading comprehension and achievement.

A wide-ranging quantitative study by Neiles (2012) investigated the effects of various reader characteristics (e.g. factual chemistry knowledge, working memory capacity, etc.) on students’ reading comprehension of chemistry texts and showed a significant correlation between reader characteristics and reading comprehension. The possession of prior knowledge of chemistry concepts positively impacts students’ understanding and explains the power of reading strategies focusing on the provision and re-activation of students’ prior knowledge for encouraging students’ reading (Salmerón et al., 2006; Taboada and Guthrie, 2006; Neiles, 2012; Ho et al., 2014).

Dori et al. (2018) evaluated the effects of context-based learning and additional metacognitive strategies used by high school students on their scientific text comprehension and chemistry understanding as reflected in their ability to identify the main subject of adapted articles as well as in explaining concepts. They found that metacognitive strategies while reading context-based adapted scientific articles can be successfully used in chemistry education, as progress in students’ conceptual chemistry understanding was demonstrated (Dori et al., 2018).

Reader-centred approaches strongly take into account the results from comprehensibility research when considering the interaction between the reader and the text and give evidence about positive effects of offensive methods to enhance students’ reading (Budd et al., 1995; Salmerón et al., 2006; Capanzana and Avilla, 2011; Leopold and Leutner, 2012; Vitale and Romance, 2012; Wang et al., 2014; Yen et al., 2018).

However, Lennox et al. (2020) draw attention to a misalignment between students’ self-reported and actual reading approaches so that many metacognitive reading strategies and the provision for students’ prior knowledge has not found its way into science education.

In our conclusion we give recommendations for chemistry teachers, chemistry teacher trainers and chemistry education researchers to address ways of improving reading in chemistry education and to show research gaps for future reading research projects.

Conclusion

Language is essential for chemistry education. There is an inextricable link between learning scientific concepts and language (Pyburn et al., 2013). Scientific literacy encompasses this link and includes students’ ability to be able to read and write (Fang, 2005). However, reading chemistry texts and textbooks poses challenges to students (Snow, 2010). The academic language in chemistry texts and textbooks and their realisation in textual and non-textual explanations demands an in-depth discussion of reading in chemistry education. The aim of our review was to give an overview of research on reading textual and non-textual explanations in chemistry texts and textbooks and draw ideas for encouraging reading in chemistry education.

In our review, recommendations for chemistry teachers and research gaps, which will guide future research endeavours of science and chemistry education researchers, appeared. We conclude by giving recommendations to both, chemistry education researchers and chemistry teachers.

Recommendations for chemistry education researchers

Reading belongs to scientific literacy and is different among various disciplines (Shanahan et al., 2011). Reading in chemistry education encompasses both, the reading of textual and non-textual explanations. Reading plays an essential role in chemistry education. Studies show correlations between students’ reading ability and chemistry performance (Korpershoek et al., 2015), question-asking (Cano et al., 2014), knowledge building (Stoffelsma and Spooren, 2019) and writing skills (Deng et al., 2019). However, more research on the effects of reading on understanding scientific concepts is necessary. Chemistry education researchers can address questions like whether there are differences among various chemistry contents, student groups, types of non-textual explanations (e.g. diagram vs. image) etc. regarding the reading styles and reading outcomes of textual and non-textual explanations so that more empirical evidence exists about factors impacting the reading in chemistry.

Chemistry textbooks are a frequently used curriculum material by science teachers (Chen and Wei, 2015) but a less favoured teaching material for students’ reading in science education (Vojíř and Rusek, 2021). Science teachers hold the language of science textbooks responsible for their infrequent use in education (Beerenwinkel and Gräsel, 2005). Studies on the use of textual teaching material and chemistry textbooks by teachers is very rare and outdated. We recommend chemistry education researchers to investigate the role of reading and textbooks in chemistry education anew. Which concrete factors do teachers hold responsible for using texts for reading in chemistry education? Are there differences between in-service and pre-service chemistry teachers and if yes, how can the findings be used to alter pre-service and in-service chemistry teachers’ education on reading and textbooks? Do chemistry teachers respond differently to traditional chemistry texts and textbooks, digital textbooks, open education resources and adapted primary literature? These questions could guide future projects of chemistry education researchers.

Science education research focused less on textual explanations in texts and textbooks. More research exists about non-textual explanations in science textbooks (Vojíř and Rusek, 2019). Both, reading textual and non-textual explanations are mutually dependent so that an integrated model in science education research on reading texts and textbooks is necessary (Taber, 2015). Research on non-textual explanations should not work to the detriment of research on textual explanations. Chemistry education researchers should focus on both equally and develop new ways to investigate the field from both perspectives.

Reading research offers two ways of evaluating chemistry texts and textbooks. Readability research analyses the text while comprehensibility research takes the readers into account (Kintsch and van Dijk, 1978). Reading research on chemistry text and textbooks was influenced by the shift from text-centred to reader-centred approaches in reading research. After readability formulas and text-inherent features had been in the foreground (Mallinson, 1951; Kennedy, 1979), comprehensibility research found its way into science education research on texts and textbooks. Nowadays, reading research on chemistry texts and textbooks primarily belongs to comprehensibility research because cognitive features, targets and interests of the readers are considered (Neiles, 2012). However, too little is known about different student groups. We recommend chemistry education researchers to follow comprehensibility research directions and methodologies and explore the field of reader-centred reading research by investigating effects of students’ ethnicity, multilingualism etc. More research on the interaction of textual and non-textual explanations and readers is necessary. Digitalisation demands other reading strategies so that reading is dependent on more than the texts and the readers. Chemistry education researchers should evaluate effects of digital reading of textual and non-textual explanations to develop new methods for encouraging reading in future chemistry education.

Our review on textual and non-textual explanations shows that both, the micro-level of texts (vocabulary and syntax) and the macro-level of texts (the organisation of texts and representations) impact students’ reading. Although research on chemistry vocabulary has a longer history in science education research than does syntax, more research is necessary for morphologically and syntactically altered chemistry texts and textbooks.

Chemistry vocabulary encompasses more than purely technical terms (Marshall et al., 1991). Dual meaning vocabulary (Song and Carheden, 2014) and non-technical words (Pickersgill and Lock, 1991) impact students’ understanding and reading of chemistry texts. Chemistry education researchers should maintain research on chemistry vocabulary. Eye-tracking methodology appears to be a useful way to design future research on chemistry vocabulary (Yun, 2021). We also recommend chemistry education researchers to measure the amount and density of chemistry vocabulary and to observe whether there appear to be differences between traditional printed textbooks and digital textbooks and open educational resources over time.

Science education research on texts and textbooks has shown less interest on syntactic structures in scientific writing. Although highly complex syntactic structures, subordinate clauses, the frequent use of passive voice and noun phrases are typical for chemistry texts and textbooks (Halliday, 1989; Fang et al., 2006; Bryce, 2013), almost no evidence exist about the impact of syntax on students’ reading of chemistry texts and textbooks. Findings rather suggest no significant impact of syntactically altered texts on students’ comprehensibility of science texts (Arya et al., 2011; Härtig et al., 2019). However, working memory theory indicates that syntactical complexity influences students’ comprehension performance (Savage et al., 2007; Swanson and O'Connor, 2009). More research is necessary on syntactically altered texts and their impact on students’ reading of chemistry texts and textbooks. Chemistry education researchers should address syntax in chemistry texts and textbooks in future projects. It seems to be the case that syntax changes when chemistry explanations move to the sub-microscopic level because describing processes on the particle level demand passive voice. This can serve as a guide for chemistry education researchers to reimpose research in the field of syntax.

Non-textual explanations gained more attention by science education research on reading, texts and textbooks (Vojíř and Rusek, 2019). Although, little evidence exist on the impact of the organisation of a text on students’ understanding of chemistry texts, more research is necessary on the effect of the organisation. Digital texts and textbooks follow other structural criteria than printed traditional texts and textbooks. Hyperlinks allow students to switch between various texts when reading digital texts. Future research of chemistry education researchers should explore this new field of reading research and should examine whether and how the organisation of digital texts impacts students’ reading of science texts.

Non-textual explanations include representations. Scientific literacy refers to both, the reading of textual explanations and representations (Kozma and Russell, 2005). Johnstone's triangle of chemistry demands students’ representational competence to understand scientific ideas and concepts (Johnstone, 1991). Much research exists in the field of representations in chemistry texts and textbooks (Enero Upahi and Ramnarain, 2019). Research shows that having more fixations on illustrations while reading texts enhances students’ comprehensibility (Hung, 2014). Text-diagram reading instruction has positive immediate effects on integrative transitions between reading textual and non-textual explanations (Jian, 2021). Research also focused on picture labelling (Mason et al., 2013) and gender differences (Huang and Chen, 2016) and chemistry education research primarily examines specific representations of chemistry like mechanistic language features of organic reaction mechanisms (Bhattacharyya, 2014) or spectra (Topczewski et al., 2017). Although much research on texts and textbooks exist for non-textual explanations, there are also research gaps to be addressed by future chemistry education researchers. Are there differences between the reading of different representations depicting the same content? How do reading textual and non-textual explanations work together in digital texts and textbooks? Which delayed effects exist for text-diagram reading instruction and are there differences between different student groups? How do secondary chemistry students read chemical representations and how can the reading be enhanced in future chemistry education?

Our review on reading textual and non-textual chemistry texts and textbooks led to the question of how to encourage reading in chemistry education. The German educational researcher, Josef Leisen, points out two ways of using texts in educational contexts (Leisen, 2020). Defensive methods approach the texts and call for simplified texts or alternative and new texts. Offensive methods focus on the reader and enable students to build up and develop reading competence on a long-term basis by enhancing students in their autonomous way of dealing with highly complex textual and non-textual explanations by being equipped with necessary reading strategies (Leisen, 2020). Much research exist in the field of defensive methods. New digital formats (McCollum, 2016), open educational resources (Sansom et al., 2021) and adapted primary literature (Phillips and Norris, 2009) show positive effects on students’ learning. However, research projects address only the meta-level of texts, like their format (printed or digital) or text type. Language is absent from research on defensive methods. Although offensive methods are the preferred way to deal with texts in chemistry education, simplified chemistry texts can help students in the first years of chemistry education (Leisen, 2020). Chemistry education researchers should examine morphologically and syntactically simplified texts and their effects on students’ understanding of scientific ideas. They should explore how simplified texts can affect students’ motivation and interests on texts and whether simplified texts allow easier ways for multilingual chemistry students to come into contact with science.

Research also shows positive effects of offensive methods for encouraging reading in science education. Reading strategies like switching between representations, drawing strategies, predicting and summarizing positively impact students’ reading of science texts (Capanzana and Avilla, 2011; Leopold and Leutner, 2012). Digitalisation will ensure new research on strategies for reading digital texts because reading a digital text demands other reading strategies than reading printed texts (Yen et al., 2018). We recommend chemistry education researchers to follow this approach and investigate new ways and methods for encouraging the reading of digital chemistry texts and textbooks. Drawing on readers’ characteristics like prior knowledge and working memory offer first encounters to explore the field of digital reading in chemistry education.

Last but not least, we recommend chemistry education researchers to find effective ways to bring reading research into future pre-service and in-service chemistry teacher education. Research in the field of language, reading and textbooks refers to the essential role reading plays in chemistry education. Chemistry education researchers must bring their findings on reading textual and non-textual explanations into teacher education programs to sustainably enhance chemistry teachers’ handling with reading in chemistry education. First ideas for designing future chemistry teacher educational programs can already be drawn from our review so that we would like to turn to recommendations for chemistry teachers now.

Recommendations for chemistry teachers

Research on language in chemistry education emphasizes the essential role of reading in chemistry education (Markic and Childs, 2016). Chemistry teachers play a major role in enhancing students’ scientific and representational literacy in chemistry education by drawing on the findings from reading research on textual and non-textual explanations in chemistry texts and textbooks (Wellington and Osborne, 2001; Seah et al., 2014).

Reading plays an important role in chemistry education and correlates with students’ chemistry performance (Korpershoek et al., 2015). Chemistry teachers should make reading a significant part of their education as they can improve students’ chemistry performance by reading.

Chemistry textbooks can be used by chemistry teachers for reading in chemistry education. Chemistry textbooks (printed and digital) and open-educational resources allow chemistry teachers to promote students’ reading of textual and non-textual explanations. Insights into readability and comprehensibility research also permit to choose reader-friendly texts and chemistry teachers can check the text and textbooks for their suitability in class. The Cloze technique can be used by chemistry teachers to choose appropriate texts and textbooks for students and to gain insights into students’ comprehensibility level of scientific texts (Bormuth, 1968).

When chemistry teachers encounter that students face difficulties with reading chemistry texts and textbooks they should draw on their knowledge about textual and non-textual explanations in chemistry texts and possible ways for encouraging the reading. Chemistry teachers should check the vocabulary of texts for its amount, density, and concordance with teachers’ language and students’ everyday language (Yager, 1983). Addressing dual meaning vocabulary helps chemistry students to properly understand technical terms (Song and Carheden, 2014). We also recommend chemistry teachers to focus on non-technical terms in chemistry texts and textbooks as research shows that students have difficulties with non-technical vocabulary in science texts (Pickersgill and Lock, 1991).

Chemistry teachers should also address the syntax of texts and can make their students aware of the meaning of subordinate clauses to express causal and conditional relations between chemical facts or make students aware of passive voice for describing the sub-microscopic level as no acting agents exist on the particle level (Kniffka and Roelcke, 2016). Complex noun phrases can be separated by chemistry teachers so that students’ working memory is relieved while reading highly sophisticated chemistry texts (Savage et al., 2007).

Chemistry teachers should also address the organisation of texts when students read chemistry texts and textbooks. Discussing together the meaning of the paragraphing of a text, the meaning of sentence connectors and interruptions in texts by representations allows students to better develop a coherent picture of a text and to integrate both, textual and non-textual explanations together (Al-Balushi and Al-Harthy, 2015). Research shows that students who are trained in text-diagram reading (Jian, 2021) and who consciously read non-textual explanations (Hsu and Yang, 2007) have a better understanding of the content so that chemistry teachers should teach their students in reading instructions that help their students during the reading of both, textual and non-textual explanations. Chemistry specific representations like chemical formulae, equations and particle images should also be addressed by chemistry teachers when students are asked to read in chemistry education (Popova and Jones, 2021).

Chemistry teachers can rely on the approach by Leisen who points our two major ways of dealing with texts in education (Leisen, 2020). Chemistry teachers can use alternative texts like adapted primary literature, digital textbooks or open educational resources to encourage reading in chemistry education (Taşdelen and Köseoğlu, 2008; Robinson et al., 2014). They can also design own simplified texts to enhance students’ reading of chemistry texts for the first time. However, we recommend chemistry teachers to follow the offensive methods for encouraging reading in chemistry education. Chemistry teachers should expand students’ prior knowledge and reading strategies to successfully and sustainably improve students’ reading of chemistry texts and textbooks (Leopold and Leutner, 2012; Ho et al., 2014). Here, chemistry teachers can rely on much evidence on positive effects of reading instructions and strategies on students’ comprehensibility (Jian, 2019).

Digital reading works differently so that new ways and methods are necessary for future reading of chemistry texts and textbooks. Chemistry teachers can enrich the research field of reading digital texts as they have the direct line to students’ challenges and difficulties when reading digital chemistry texts and textbooks.

Author contributions

David Meyer: investigation, conceptualization, writing – original draft; Verena Pietzner: conceptualization, supervision, writing – review and editing.

Conflicts of interest

There are no conflicts of interest to declare.

Acknowledgements

This project is part of the “Qualitätsoffensive Lehrerbildung”, a joint initiative of the Federal Government and the Länder which aims to improve the quality of teacher training. The programme is funded by the Federal Ministry of Education and Research. The authors are responsible for the content of this publication.

References

1. Al-Balushi S. M. and Al-Harthy I. S., (2015), Students' mind wandering in macroscopic and submicroscopic textual narrations and its relationship with their reading comprehension. Chem. Educ. Res. Pract., 16(3), 680–688 10.1039/C5RP00052A.
2. Allen G., Guzman-Alvarez A., Smith A., Gamage A., Molinaro M. and Larsen D. S., (2015), Evaluating the effectiveness of the open-access ChemWiki resource as a replacement for traditional general chemistry textbooks, Chem. Educ. Res. Pract., 16(4), 939–948 10.1039/C5RP00084J.
3. Ariasi N. and Mason L., (2014), From covert processes to overt outcomes of refutation text reading: The interplay of science text structure and working memory capacity through eye fixations, Int. J. Sci. Math. Educ., 12, 493–523.
4. Arya D. J., Hiebert E. H. and David Pearson P., (2011), The effects of syntactic and lexical complexity on the comprehension of elementary science texts, Int. Electron. J. Elem. Educ., 4(1), 107–125.
5. Atkinson M. B., Croisant M. and Bretz S. L., (2021), Investigating first-year undergraduate chemistry students’ reasoning with reaction coordinate diagrams when choosing among particulate-level reaction mechanisms, Chem. Educ. Res. Pract., 22(1), 199–213 10.1039/D0RP00193G.
6. Bailin A. and Grafstein A., (2016), Readability: Text and Context, Basingstoke: Palgrave Macmillan.
7. Bansiong A. J., (2019), Readability, content, and mechanical feature analysis of selected commercial science textbooks intended for third grade filipino learners, Cogent Educ., 6(1), 1706395 DOI:10.1080/2331186X.2019.1706395.
8. Becker M. L. and Nilsson M. R., (2021), College chemistry textbooks fail on gender representation, J. Chem. Educ., 98(4), 1146–1151 DOI:10.1021/acs.jchemed.0c01037.
9. Beerenwinkel A. and Gräsel C., (2005), Texte im Chemieunterricht: Ergebnisse einer Befragung von Lehrkräften, Z. Didaktik Naturwissenschaften, 11, 21–39.
10. Beier S., Berlow S., Boucaud E., Bylinskii Z., Cai T. and Cohn J. et al., (2021), Readability Research: An Interdisciplinary Approach DOI:10.48550/arXiv.2107.09615.
11. Bergqvist A., Drechsler M., Jong O. de and Rundgren S.-N. C., (2013), Representations of chemical bonding models in school textbooks – Help or hindrance for understanding? Chem. Educ. Res. Pract., 14(4), 589–606 10.1039/C3RP20159G.
12. Bhattacharyya G., (2014), Trials and tribulations: Student approaches and difficulties with proposing mechanisms using the electron-pushing formalism, Chem. Educ. Res. Pract., 15(4), 594–609 10.1039/C3RP00127J.
13. Biber D., (2019), Grammatical Complexity in Academic English: Linguistic Change in Writing, 2nd edn, Cambridge: Cambridge University Press.
14. Biber D. and Gray B., (2010), Challenging stereotypes about academic writing: Complexity, elaboration, explicitness, J. Engl. Acad. Purposes, 9(1), 2–20.
15. Biber D. and Gray B., (2021), Nominalizing the verb phrase in academic science writing, in Biber D., Gray B., Staples S. and Egbert J. (eds), The Register-Functional Approach to Grammatical Complexity, New York, NY: Routldge.
16. Biber D., Conrad S. and Cortes V., (2004), If you look at…: Lexical bundles in university teaching and textbooks, Appl. Ling., 25(3), 371–405.
17. Bintang Nadea A. B., Jumariati and Nasrullah, (2021), Bottom-up or top-down reading strategies: Reading strategies used by EFL students, Adv. Soc. Sci., Educ. Hum. Res., 587, 30–36 DOI:10.2991/assehr.k.211021.005.
18. Bongers A., Northoff G. and Flynn A. B., (2019), Working with mental models to learn and visualize a new reaction mechanism, Chem. Educ. Res. Pract., 20(3), 554–569 10.1039/C9RP00060G.
19. Bormuth J. R., (1968), Cloze test readability: Criterion reference scores, J. Educ. Meas., 5(3), 189–196.
20. Bryce N., (2013), Textual features and language demands of primary grade science textbooks: The call for more informational texts in primary grades, in: Khine M. S., (ed.), Critical Analysis of Science Textbooks: Evaluating instructional effectiveness, Dordrecht: Springer Netherlands, pp. 101–122.
21. Budd D., Whitney P. and Turley K. J., (1995), Individual differences in working memory strategies for reading expository text, Mem. Cogn., 23(6), 735–748 DOI:10.3758/bf03200926.
22. Canac S. and Kermen I., (2016), Exploring the mastery of French students in using basic notions of the language of chemistry, Chem. Educ. Res. Pract., 17(3), 452–473 10.1039/C6RP00023A.
23. Cano F., García Á., Berbén A. and Justicia F., (2014), Science learning: A path analysis of its links with reading comprehension, question-asking in class and science achievement, Int. J. Sci. Educ., 36(10), 1710–1732 DOI:10.1080/09500693.2013.876678.
24. Capanzana C. O. and Avilla R. A., (2011), Reciprocal teaching approach with self-regulated learning (RT-SRL): Effects on students’ reading comprehension, achievement and self-regulation in chemistry, Normal Lights, 11(2), 31–59.
25. Carver R. P., (1994), Percentage of unknown vocabulary words in text as a function of the relative difficulty of the text: Implications for instruction, J. Reading Behav., 26(4), 413–437.
26. Cassels J. R. T. and Johnstone A. H., (1985), Words That Matter in Science: a report of a research exercise, London: The Royal Society of Chemistry.
27. Cervetti G. N., Hiebert E. H., Pearson P. D. and McClung N. A., (2015), Factors that influence the difficulty of science words, J. Lit. Res., 47(2), 153–185 DOI:10.1177/1086296X15615363.
28. Chang H., Duncan K., Kim K. and Paik S.-H., (2020), Electrolysis: What textbooks don’t tell us, Chem. Educ. Res. Pract., 21(3), 806–822 10.1039/C9RP00218A.
29. Chen B. and Wei B., (2015), Examining chemistry teachers' use of curriculum materials: In view of teachers' pedagogical content knowledge, Chem. Educ. Res. Pract., 16(2), 260–272 10.1039/C4RP00237G.
30. Chiang-Soong B. and Yager R. E., (1993), Readability levels of the science textbooks most used in secondary schools, Sch. Sci. Math., 93(1), 24–27.
31. Childs P. E. and O'Farrell J., (2003), Learning science through English: An investigation of the vocabulary skills of native and non-native english speakers in international schools, Chem. Educ. Res. Pract., 4(3), 233–247.
32. Connor M. C., Glass B. H. and Shultz G. V., (2021), Development of the NMR lexical representational competence (NMR-LRC), instrument as a formative assessment of lexical ability in 1H NMR spectroscopy, J. Chem. Educ., 98(9), 2786–2798 DOI:10.1021/acs.jchemed.1c00332.
33. Conrad S., (2019), Register in english for academic purposes and english for specific purposes, Register Stud., 1(1), 168–198.
34. Cummins J., (1979), Cognitive/academic language proficiency, linguistic interdependence, the optimum age question and some other matters, Work. Pap. Biling., 19, 197–205.
35. Dağlı Gökbulut Ö. and Güneyli A., (2019), Printed versus electronic texts in inclusive environments: Comparison research on the reading comprehension skills and vocabulary acquisition of special needs students, Educ. Sci., 9(3), 246 DOI:10.3390/educsci9030246.
36. Dambacher M., (2010), Bottom-up and top-down processes in reading: Influences of frequency and predictability on event-related potentials and eye movements, Potsdam: Universitätsverlag Potsdam.
37. Danili E. and Reid N., (2006), Cognitive factors that can potentially affect pupils’ test performance, Chem. Educ. Res. Pract., 7(2), 64–83 10.1039/B5RP90016F.
38. Deng Y., Kelly G. J. and Deng S., (2019), The influences of integrating reading, peer evaluation, and discussion on undergraduate students’ scientific writing, Int. J. Sci. Educ., 41(10), 1408–1433 DOI:10.1080/09500693.2019.1610811.
39. D'Mello S. K. and Mills C. S., (2021), Mind wandering during reading: An interdisciplinary and integrative review of psychological, computing, and intervention research and theory, Lang. Ling. Compass, 15(4) DOI:10.1111/lnc3.12412.
40. Dori Y. J., Avargil S., Kohen Z. and Saar L., (2018), Context-based learning and metacognitive prompts for enhancing scientific text comprehension, Int. J. Sci. Educ., 40(10), 1198–1220 DOI:10.1080/09500693.2018.1470351.
41. Dubin F. and Bycina D., (1991), Models of the process of reading, in Celce-Murcia (ed.), Teaching English as a Second or Foreign Language, Boston, Mass: Heinle and Heinle.
42. Enero Upahi J. and Ramnarain U., (2019), Representations of chemical phenomena in secondary school chemistry textbooks, Chem. Educ. Res. Pract., 20(1), 146–159 10.1039/C8RP00191J.
43. Fang Z., (2005), Scientific literacy: A systemic functional linguistics perspective, Sci. Educ., 89(2), 335–347 DOI:10.1002/sce.20050.
44. Fang Z., Schleppegrell M. J. and Cox B. E., (2006), Understanding the language demands of schooling: Nouns in academic registers, J. Lit. Res., 38(3), 247–273.
45. Fatoba J. O., (2014), Readability level of recommended chemistry textbooks and students’ academic performance in senior secondary schools in Ekiti State, Nigeria, Int. J. Educ. Res., 2(9), 41–50.
46. Finkenstaedt-Quinn S. A., Petterson M., Gere A. and Shultz G., (2021), Praxis of writing-to-learn: A model for the design and propagation of writing-to-learn in STEM, J. Chem. Educ., 98(5), 1548–1555 DOI:10.1021/acs.jchemed.0c01482.
47. Fitzgerald W. J., Elmore J., Kung M. and Stenner A. J., (2017), The Conceptual complexity of vocabulary in elementary-grades core science program textbooks, Reading Res. Q., 52(4), 417–442 DOI:10.1002/rrq.184.
48. Galloway K. R., Stoyanovich C. and Flynn A. B., (2017), Students’ interpretations of mechanistic language in organic chemistry before learning reactions, Chem. Educ. Res. Pract., 18(2), 353–374 10.1039/C6RP00231E.
49. Gkitzia V., Salta K. and Tzougraki C., (2020), Students’ competence in translating between different types of chemical representations, Chem. Educ. Res. Pract., 21(1), 307–330 10.1039/C8RP00301G.
50. Graulich N. and Caspari I., (2021), Designing a scaffold for mechanistic reasoning in organic chemistry, Chem. Teach. Int., 3(1), 19–30 DOI:10.1515/cti-2020-0001.
51. Gray B., (2021), On the complexity of academic writing, in Biber D., Gray B., Staples S. and Egbert J., (ed.), The Register-Functional Approach to Grammatical Complexity, New York, NY: Routldge.
52. Groves F. H., (1995), Science vocabulary load of selected secondary science textbooks, Sch. Sci. Math., 95(5), 231–235.
53. Groves F. H., (2016), A longitudinal study of middle and secondary level science textbook vocabulary loads, Sch. Sci. Math., 116(6), 320–325.
54. Halliday M. A. K., (1989), Some grammatical problems in Scientific English, Australian Rev. Appl. Ling., 5(6), 13–37.
55. Härtig H., Bernholt S., Prechtl H. and Retelsdorf J., (2015), Unterrichtssprache im Fachunterricht – Stand der Forschung und Forschungsperspektiven am Beispiel des Textverständnisses, Z. Didaktik Naturwissenschaften, 21(1), 55–67 DOI:10.1007/s40573-015-0027-7.
56. Härtig H., Fraser N., Bernholt S. and Retelsdorf J., (2019), Kann man Sachtexte vereinfachen? – Ergebnisse einer Generalisierungsstudie zum Textverständnis, Z. Didaktik Naturwissenschaften, 25(1), 273–287 DOI:10.1007/s40573-019-00105-7.
57. Hiebert E. H., Scott J. A., Castaneda R. and Spichtig A., (2019), An analysis of the features of words that influence vocabulary difficulty, Educ. Sci., 9(1), 8 DOI:10.3390/educsci9010008.
58. Ho H. N. J., Tsai M.-J., Wang C.-Y. and Tsai C.-C., (2014), Prior knowledge and online inquiry-based science reading: Evidence from Eye Tracking. Int. J. Sci. Math. Educ., 12, 524–554.
59. Hsu P.-L. and Yang W.-G., (2007), Print and image integration of science texts and reading comprehension: A systemic functional linguistics perspective, Int. J. Sci. Math. Educ., 5(4), 639–659.
60. Huang P.-S. and Chen H.-C., (2016), Gender differences in eye movements in solving text-and-diagram science problems, Int. J. Sci. Math. Educ., 14(2), 327–346 DOI:10.1007/s10763-015-9644-3.
61. Hung Y.-N., (2014), “What are you looking at?” An eye movement exploration in science text reading, Int. J. Sci. Math. Educ., 12(2), 241–260.
62. Jian Y.-C., (2019), Reading instructions facilitate signaling effect on science text for young readers: An eye-movement study, Int. J. Sci. Math. Educ., 17(3), 503–522 DOI:10.1007/s10763-018-9878-y.
63. Jian Y.-C., (2021), The immediate and delayed effects of text–diagram reading instruction on reading comprehension and learning processes: evidence from eye movements, Reading Writ., 34(3), 727–752 DOI:10.1007/s11145-020-10089-3.
64. Jian Y.-C., (2022), Influence of science text reading difficulty and hands-on manipulation on science learning: An eye-tracking study, J. Res. Sci. Teach., 59(3), 358–382 DOI:10.1002/tea.21731.
65. Johnstone A. H., (1991), Why is science difficult to learn? Things are seldom what they seem, J. Comput. Assist. Learn., 7, 75–83.
66. Johnstone A. H. and Selepeng D., (2001), A language problem revisited, Chem. Educ. Res. Pract., 2(1), 19–29.
67. Kennedy K., (1979), Who's afraid of readability scales? Selecting high school science texts, Curric. Rev., 18(3), 231–234.
68. Kintsch W. and van Dijk T., (1978), Towards a model of text comprehension and production, Psychol. Rev., 18(3), 231–234.
69. Kniffka G. and Roelcke T. D., (2016), Fachsprachenvermittlung im Unterricht, Paderborn: Schöningh.
70. Korpershoek H., Kuyper H. and van der Werf G., (2015), The relation between students’ math and reading ability and their mathematics, physics, and chemistry examination grades in secondary education, Int. J. Sci. Math. Educ., 13(5), 1013–1037.
71. Kozma R. and Russell J., (2005), Students becoming chemists: developing representational competence, in Gilbert J. K., (ed.), Visualization in Science Education, Dordrecht: Springer, pp. 121–146.
72. Larkin J. H. and Simon H. A., (1987), Why a diagram is (sometimes), worth ten thousand words, Cogn. Sci., 11, 65–100 DOI:10.1111/j.1551-6708.1987.tb00863.x.
73. Larsen D. S., Russay R., Belford R., Kennepohl D., Bennett D. and Soult A. et al., (2017), Come Join the Party! Recent Progress of The Community Based LibreTexts (née ChemWiki), Project, available from: https://confchem.ccce.divched.org/2017SpringCCCENLP5.
74. Lee E. N. and Orgill M., (2022), Toward equitable assessment of english language learners in general chemistry: Identifying supportive features in assessment items. J. Chem. Educ., 99(1), 35–48 DOI:10.1021/acs.jchemed.1c00370.
75. Lee O., Quinn H. and Valdés G., (2013), Science and language for english language learners in relation to next generation science standards and with implications for common core state standards for english language arts and mathematics, Educ. Res., 42(4), 223–233 DOI:10.3102/0013189X13480524.
76. Leisen J., (2020), Handbuch Lesen im Fachunterricht, Stuttgart: Ernst Klett Sprachen.
77. Lembens A., Hammerschmid S., Jaklin-Farcher S., Nosko C. and Reiter K., (2019), Textbooks as source for conceptional confusion in teaching and learning ‘acids and bases’ in lower secondary school, Chem. Teach. Int., 1(2) DOI:10.1515/cti-2018-0029.
78. Lennox R., Hepburn K., Leaman E. and van Houten N., (2020), ‘I’m probably just gonna skim’: An assessment of undergraduate students’ primary scientific literature reading approaches, Int. J. Sci. Educ., 42(9), 1409–1429 DOI:10.1080/09500693.2020.1765044.
79. Leopold C. and Leutner D., (2012), Science text comprehension: Drawing, main idea selection, and summarizing as learning strategies, Learn. Instruct., 22(1), 16–26 DOI:10.1016/j.learninstruc.2011.05.005.
80. Liu Y. and Taber K. S., (2016), Analysing symbolic expressions in secondary school chemistry: their functions and implications for pedagogy, Chem. Educ. Res. Pract., 17(3), 439–451 10.1039/C6RP00013D.
81. Mallinson G. G., (1951), The readability of high school science texts, Sci. Teach., 18(5), 253–256.
82. Mallinson G. G., Sturm H. E. and Mallinson L. M., (1952), The reading difficulty of textbooks for high-school chemistry, J. Chem. Educ., 29(12), 629–631 DOI:10.1021/ed029p629.
83. Markic S. and Childs P. E., (2016), Language and the teaching and learning of chemistry, Chem. Educ. Res. Pract., 17(3), 434–438 10.1039/C6RP90006B.
84. Marshall S., Gilmour M. and Lewis D., (1991), Words that matter in science and technology, Res. Sci. Technol. Educ., 9(1), 5–16 DOI:10.1080/0263514910090102.
85. Mason L., Pluchino P. and Tornatora M. C., (2013), Effects of picture labeling on science text processing and learning: Evidence from eye movements, Reading Res. Q., 48(2), 199–214 DOI:10.1002/rrq.41.
86. Mayer R. E., (ed.), (2014), The Cambridge Handbook of Multimedia Learning, 2nd edition, Cambridge: Cambridge University Press.
87. McCarthy C. P., (1999), Reading theory as a microcosm of the four skills, Appl. Ling. Ser., 3–8.
88. McCollum B. M., (2016), Improving academic reading habits in chemistry through flipping with an open education digital textbook, in Schultz M., Schmid S. and Holme T. (ed.), Technology and Assessment Strategies for Improving Student Learning in Chemistry, pp. 23–45.
89. Merzyn G., (1987), The language of school science, Int. J. Sci. Educ., 9(4), 483–489 DOI:10.1080/0950069870090406.
90. Meyerson M. J., Ford M., Jones W. and Ward M., (1991), Science vocabulary knowledge of third and fifth grade students, Sci. Educ., 75(4), 419–428.
91. Moundy K., Chafiq N. and Talbi M., (2021), Comparative analysis of student engagement in digital textbook use during quarantine, Educ. Sci., 11(7), 352 DOI:10.3390/educsci11070352.
92. Muspratt S. and Freebody P., (2013), Unterstanding the disciplines of science: Analysing the language of science textbooks, in Khine M. S. (ed.), Critical Analysis of Science Textbooks: Evaluating instructional effectiveness, Dordrecht: Springer Netherlands, pp. 33–60.
93. Neiles K. Y., (2012), An Investigation of the Effects of Reader Characteristics on Reading Comprehension of a General Chemistry Text, Thesis (PhD), Washington, DC: The Catholic University of America.
94. Nigro R. G. and Trivelato S. F., (2012), Knowledge, its application, and attitudes associated with the reading of diverse genres of science texts, Int. J. Sci. Educ., 34(16), 2529–2564 DOI:10.1080/09500693.2012.711916.
95. Norris S. P. and Phillips L. M., (2003), How literacy in its fundamental sense is central to scientific literacy, Sci. Educ., 87(2), 224–240 DOI:10.1002/sce.10066.
96. Nunan D., (1991), Language Teaching Methodology, Hertfordshire: Prentice Hall International.
97. Nyachwaya J. M., (2016), General chemistry students' conceptual understanding and language fluency: Acid–base neutralization and conductometry, Chem. Educ. Res. Pract., 17(3), 509–522 10.1039/C6RP00015K.
98. O'Brien D. G. and Stewart R. A., (1990), Preservice teachers' perspectives on why every teacher is not a teacher of reading: A qualitative analysis, J. Reading Behav., 22(2), 101–129 DOI:10.1080/10862969009547699.
99. Okanlawon A. E., (2011), Using appropriate strategies to improve students' comprehension of chemistry texts: A guide for chemistry teachers, Afr. Res. Rev., 5(4), 214–230.
100. Parobek A. P., Chaffin P. M. and Towns M. H., (2021), Location-thinking, value-thinking, and graphical forms: Combining analytical frameworks to analyze inferences made by students when interpreting the points and trends on a reaction coordinate diagram, Chem. Educ. Res. Pract., 22(3), 697–714 10.1039/D1RP00037C.
101. Phillips L. M. and Norris S. P., (2009), Bridging the gap between the language of science and the language of school science through the use of adapted primary literature, Res. Sci. Educ., 39(3), 313–319 DOI:10.1007/s11165-008-9111-z.
102. Pickersgill S. and Lock R., (1991), Student understanding of selected non-technical words in science, Res. Sci. Technol. Educ., 9(1), 71–79 DOI:10.1080/0263514910090107.
103. Popova M. and Jones T., (2021), Chemistry instructors’ intentions toward developing, teaching, and assessing student representational competence skills, Chem. Educ. Res. Pract., 22(3), 733–748 10.1039/D0RP00329H.
104. Pyburn D. T., Pazicni S., Benassi V. A. and Tappin E. E., (2013), Assessing the relation between language comprehension and performance in general chemistry, Chem. Educ. Res. Pract., 14(4), 524–541 10.1039/C3RP00014A.
105. Rapp D. N., (2001), Effect of textbook readability on student achievement in high school chemistry, Indiana Reading J., 33(3), 26–36.
106. Rees S. W., Kind V. and Newton D., (2018), Can language focussed activities improve understanding of chemical language in non-traditional students? Chem. Educ. Res. Pract., 19(3), 755–766 10.1039/C8RP00070K.
107. Reid N., (2021), The Johnstone Triangle: The Key to Understanding Chemistry, London: Royal Society of Chemistry.
108. Robinson T. J., Fischer L., Wiley D. and Hilton J., (2014), The impact of open textbooks on secondary science learning outcomes, Educ. Res., 43(7), 341–351 DOI:10.3102/0013189X14550275.
109. Rumelhart D. E., (1977), Toward an interactive model of reading, in Dornič S., (ed.), Attention and performance: VI. Proceedings of the Sixth International Symposium on Attention and Performance, International Symposium on Attention and Performance, July 28-August 1, 1975, Stockholm, Sweden. Lawrence Erlbaum.
110. Ryoo K., Bedell K. and Swearingen A., (2018), Promoting linguistically diverse students’ short-term and long-term understanding of chemical phenomena using visualizations, J. Sci. Educ. Technol., 27(6), 508–522 DOI:10.1007/s10956-018-9739-z.
111. Salmerón L., Kintsch W. and Cañas J. J., (2006), Reading strategies and prior knowledge in learning from hypertext, Mem. Cogn., 34(5), 1157–1171 DOI:10.3758/bf03193262.
112. Sansom R. L., Clinton-Lisell V. and Fischer L., (2021), Let students choose: Examining the impact of open educational resources on performance in general chemistry, J. Chem. Educ., 98(3), 745–755 DOI:10.1021/acs.jchemed.0c00595.
113. Savage R., Lavers N. and Pillay V., (2007), Working memory and reading difficulties: What we know and what we don’t know about the relationship, Educ. Psychol. Rev., 19(2), 185–221 DOI:10.1007/s10648-006-9024-1.
114. Scheppegrell M. J., (2001), Linguistic features of the language of schooling, Ling. Educ., 12(4), 431–459.
115. Schraw G. and Dennison R. S., (1994), The effect of reader purpose on interest and recall, J. Reading Behav., 26(1), 1–18.
116. Seah L. H., (2016), Elementary teachers’ perception of language issues in science classrooms, Int. J. Sci. Math. Educ., 14(6), 1059–1078 DOI:10.1007/s10763-015-9648-z.
117. Seah L. H., Clarke D. J. and Hart C. E., (2014), Understanding the language demands on science students from an integrated science and language perspective, Int. J. Sci. Educ., 36(6), 952–973 DOI:10.1080/09500693.2013.832003.
118. Shanahan T. and Shanahan C., (2008), Teaching disciplinary literacy to adolescents: Rethinking content- area literacy, Harv. Educ. Rev., 78(1), 40–59.
119. Shanahan C., Shanahan T. and Misischia C., (2011), Analysis of expert readers in three disciplines, J. Lit. Res., 43(4), 393–429 DOI:10.1177/1086296X11424071.
120. Skagen D., McCollum B., Morsch L. and Shokoples B., (2018), Developing communication confidence and professional identity in chemistry through international online collaborative learning, Chem. Educ. Res. Pract., 19(2), 567–582 10.1039/C7RP00220C.
121. Snow C. E., (2010), Academic language and the challenge of reading for learning about science, Science, 328(5977), 450–452 DOI:10.1126/science.1182597.
122. Song Y. and Carheden S., (2014), Dual meaning vocabulary (DMV), words in learning chemistry, Chem. Educ. Res. Pract., 15(2), 128–141 10.1039/C3RP00128H.
123. Stoffelsma L. and Spooren W., (2019), The relationship between english reading proficiency and academic achievement of first-year science and mathematics students in a multilingual context, Int. J. Sci. Math. Educ., 17(5), 905–922 DOI:10.1007/s10763-018-9905-z.
124. Sumfleth E., (1995), Linguistische Textverständlichkeitskriterien. Helfen Sie bei der Darstellung chemischer Inhalte? Chemkon, 1(1), 167–171.
125. Sumfleth E., (1996), Chemie verstehbar und verständlich – Anspruch und Wirklichkeit, Chemkon, 3(4), 55–72.
126. Swanson H. L. and O'Connor R., (2009), The role of working memory and fluency practice on the reading comprehension of students who are dysfluent readers, J. Learn. Disabil., 42(6), 548–575 DOI:10.1177/0022219409338742.
127. Taber K. S., (2015), Exploring the language(s), of chemistry education, Chem. Educ. Res. Pract., 16(2), 193–197 10.1039/C5RP90003D.
128. Taboada A. and Guthrie J. T., (2006), Contributions of student questioning and prior knowledge to construction of knowledge from reading information text, J. Lit. Res., 38(1), 1–35.
129. Taşdelen U. and Köseoğlu F., (2008), Learner-friendly textbooks: Chemistry texts based on a constructivist view of learning, Asia Pac. Educ. Rev., 9(2), 136–147.
130. Thiele R. B. and Treagust D. F., (1995), Analogies in chemistry textbooks, Int. J. Sci. Educ., 17(6), 783–795 DOI:10.1080/0950069950170609.
131. To V. and Mahboob A., (2019), Complexity of english textbook language: A systemic functional analysis, Ling. Hum. Sci., 13(3).
132. Topczewski J. J., Topczewski A. M., Tang H., Kendhammer L. K. and Pienta N. J., (2017), NMR spectra through the eyes of a student: Eye tracking applied to NMR items, J. Chem. Educ., 94(1), 29–37 DOI:10.1021/acs.jchemed.6b00528.
133. Tóthová M., Rusek M. and Chytrý V., (2021), Students’ procedure when solving problem tasks based on the periodic table: An eye-tracking study, J. Chem. Educ., 98(6), 1831–1840 DOI:10.1021/acs.jchemed.1c00167.
134. Tseng Y.-J., Hong Z.-R. and Lin H., (2022), Advancing students’ scientific inquiry performance in chemistry through reading and evaluative reflection, Chem. Educ. Res. Pract 10.1039/D1RP00246E.
135. Udu T. T., Gyuse E. Y., Samba R. M. O. and Iortim S., (2016), Readability characteristics of nigerian science textbooks as a factor of students’ science achievement, ICSHER J., 2(2), 1–13.
136. Vitale M. R. and Romance N. R., (2012), Using in-depth science instruction to accelerate student achievement in science and reading comprehension in grades 1–2, Int. J. Sci. Math. Educ., 10, 457–472.
137. Vojíř K. and Rusek M., (2019), Science education textbook research trends: a systematic literature review, Int. J. Sci. Educ., 41(11), 1496–1516 DOI:10.1080/09500693.2019.1613584.
138. Vojíř K. and Rusek M., (2021), Preferred chemistry curriculum perspective: Teachers’ perception of lower-secondary school textbooks, J. Baltic Sci. Educ., 20(2), 316–331 DOI:10.33225/jbse/21.20.316.
139. Vygotsky L., (1987), Thought and Language, 2nd edition, MIT Press: Cambridge, Mass.
140. Wang J.-R., Chen S.-F., Fang I. and Chou C.-T., (2014), Comparison of Taiwanese and Canadian Students' metacognitive awareness of science reading, text, and strategies, Int. J. Sci. Educ., 36(4), 693–713 DOI:10.1080/09500693.2013.826841.
141. Watts F. M., Park G. Y., Petterson M. N. and Shultz G. V., (2022), Considering alternative reaction mechanisms: Students’ use of multiple representations to reason about mechanisms for a writing-to-learn assignment, Chem. Educ. Res. Pract 10.1039/D1RP00301A.
142. Wellington J. and Osborne J., (2001), Language and Literacy in Science Education, Philadelphia, PA: Open University Press.
143. Wright K. L., Franks A. D., Kuo L.-J., McTigue E. M. and Serrano J., (2016), Both theory and practice: Science literacy instruction and theories of reading, Int. J. Sci. Math. Educ., 14(7), 1275–1292 DOI:10.1007/s10763-015-9661-2.
144. Yager R. E., (1983), The importance of terminology in teaching K-12 science, J. Res. Sci. Teach., 20(6), 577–588.
145. Yen M.-H., Wang C.-Y., Chang W.-H., Chen S., Hsu Y.-S. and Liu T.-C., (2018), Assessing metacognitive components in self-regulated reading of science texts in E-based environments, Int. J. Sci. Math. Educ., 16(5), 797–816 DOI:10.1007/s10763-017-9818-2.
146. Yore L. D., (1991), Secondary science teachers' attitudes toward and beliefs about science reading and science textbooks, J. Res. Sci. Teach., 28(1), 55–72.
147. Yun E., (2021), Comparing the reading behaviours of students with high- and low-level comprehension of scientific terms by eye movement analysis, Res. Sci. Educ., 51(4), 939–956 DOI:10.1007/s11165-020-09935-9.
148. Yun E. and Park Y., (2018), Extraction of scientific semantic networks from science textbooks and comparison with science teachers’ spoken language by text network analysis, Int. J. Sci. Educ., 40(17), 2118–2136 DOI:10.1080/09500693.2018.1521536.

---