View PDF VersionPrevious ArticleNext Article
 
DOI: 10.1039/C9RP00201D (Paper) Chem. Educ. Res. Pract., 2020, 21, 570-581

Investigating perceptions of the structure and development of scientific knowledge in the context of a transformed organic chemistry lecture course

A. A. Flaherty
School of Education, University of Limerick, Ireland. E-mail: Aishling.flaherty@ul.ie

Received 4th September 2019 , Accepted 22nd January 2020

First published on 23rd January 2020

Abstract

Organic Chemistry, Life, the Universe and Everything (OCLUE) is an undergraduate lecture-based organic chemistry course that has been transformed in line with the vision for science education set out by the ‘Framework for K-12 Science Education: Practices, Crosscutting Concepts and Core Ideas’ (National Research Council, 2012). OCLUE is designed to progress students understanding of core ideas in organic chemistry through the use of scientific practices such as constructing explanations, predictions and models. The purpose of this study is to generate theory on how OCLUE students conceptualise the structure and development of scientific knowledge. Eleven students with diverse experiences and exam performances were interviewed. The data was collected and analysed in accordance with the tenants of constructivist grounded theory (Charmaz, 2000). OCLUE students conceptualised a hierarchical structure of scientific knowledge whereby behind claims and answers in science is important information that determines the validity of the claim or answer. Being adept in utilising this information was important to students in OCLUE as it provided them with the opportunity to account for why phenomena occur in organic chemistry. Students explained that the process of developing scientific knowledge is rarely straight-forward or pre-determined. Instead it was believed that scientists needed to piece together what they know in seemingly random ways in order to solve science puzzles. In the context of OCLUE, students explained that memorising information ahead of OCLUE exams was insufficient. Instead they had to synthesise and interrogate their prior understanding to figure out new problems encountered in OCLUE exams. Students attributed the efficacy of OCLUE's pedagogy to helping them engage in constructivist thinking processes that involved interrogating and applying their prior knowledge. This contributes to the understanding that OCLUE has set out a precedent organic chemistry course that can foster a more scientific way of learning science that contrasts students’ engagement in considerably arduous memorisation techniques.

Context

Transforming STEM education

The calls to transform undergraduate Science, Technology, Engineering, and Mathematics (STEM) education are long-standing (Havighurst, 1929; Lloyd and Spencer, 1994; National Research Council, 1999; Cooper, 2010; Cooper and Klymkowsky, 2013; Otero and Meltzer, 2016). It is becoming increasingly imperative to improve undergraduate STEM education in order to combat a range of issues facing higher education around the world such as the need to improve STEM retention rates in the United States of America (Olson and Riordan, 2012) and to respond to the demands for highly-skilled professionals working in STEM-related occupations in Europe (Shapiro et al., 2015).

Towards improving science and engineering education in the United States of America, the ‘Framework for K-12 Science Education: Practices, Crosscutting Concepts and Core Ideas’ has set out an ambitious vision for educators (National Research Council, 2012). In an attempt to address curricular deficiencies such as the emphasis of discrete facts with a focus on breath over depth and the lack of opportunities for students to experience how science is actually done, the Framework seeks to harness the power of integration. Here, learning in science is sought to be achieved through the integration of three dimensions: disciplinary core ideas, scientific and engineering practices, and crosscutting concepts. Scientific practices are specific, well-defined ways in which scientists can use their knowledge such as constructing models, explanations and arguments, analysing and interpreting data, and mathematical reasoning (Cooper, 2016). Core ideas are concepts which are central to the content of a discipline and can be used to help generate insight into phenomena associated with particular disciplines. Finally, crosscutting concepts are lenses in which the integration of scientific practices and core ideas can be operated. The integration of scientific practices, core ideas and cross cutting concepts is commonly referred to as three-dimensional learning (3DL).

Organic chemistry, life, the universe and everything (OCLUE)

The Organic Chemistry, Life, the Universe and Everything (OCLUE) is an undergraduate lecture-based organic chemistry course developed in line with the 3DL vision set out by the Framework (National Research Council, 2012; Cooper et al., 2019). In OCLUE, a conscious effort is made to connect everything that students are taught to four core ideas in organic chemistry: structure–property relationships, bonding and interactions, energy, and stability and change. Students’ understanding of these core ideas is carefully progressed by facilitating students’ engagement in scientific practices such as asking questions, designing and carrying out investigations, analysing and interpreting data, constructing and using models, mathematical and computational thinking, constructing explanations, engaging in argumentation, and evaluating and communicating information. This pedagogical anchor serves to deliver a learning experience that encourages students to use their knowledge, rather than engaging in rote memorisation and regurgitation techniques (National Research Council, 2012; Cooper et al., 2019).

OCLUE stems from earlier work on its associated general chemistry course, Chemistry, Life, the Universe and Everything (CLUE) (Cooper and Klymkowsky, 2013) which is built on the same premise as OCLUE. Several studies provide evidence for the efficacy of CLUE in supporting student understanding and reasoning about a range of chemical phenomena. For example, compared to students taught in traditional courses, CLUE students can use chemical structure to predict chemical and physical properties at least one semester earlier (Underwood et al., 2016); CLUE students are significantly more likely to indicate correctly that intermolecular forces occur between, rather than within small molecules (Williams et al., 2015); and finally, CLUE students are significantly more likely to draw Lewis structures and derive the important information contained within Lewis Structures (Cooper et al., 2012). Additionally students from a CLUE general chemistry course are better able to reason about acid base reactions, and this improvement is continued through two semesters of a traditional organic chemistry course (Crandell et al., 2018). However, the majority of this research on the efficacy of CLUE and OCLUE courses in facilitating advancements in students’ learning is quantitative in nature. Therefore this research set out to learn more about how students enrolled in OCLUE conceptualise the structure and development of scientific knowledge using qualitative methods.

The structure and development of scientific knowledge

According to Kuhn, a revolution in science involves the establishment of new scientific knowledge following the address of serious anomalies in pre-existing scientific knowledge (Kuhn, 2012, p. xi). The time in which these anomalies are addressed by scientists is referred to as a period of crisis, in which new ideas are reconstructed towards developing new scientific knowledge. This new scientific knowledge is thought to be incommensurate to the pre-existing knowledge, meaning that both new and pre-existing bodies of scientific knowledge are so different, they cannot be compared (Kuhn, 2012).

In contrast to Kuhn, Piaget theorises a more continuous model of scientific knowledge development (Piaget et al., 1985; Piaget and Garcia, 1989; Tsou, 2006). Instead of disregarding pre-existing scientific knowledge, Piaget and Garcia (1989) argue that this pre-existing scientific knowledge is quintessential in laying the foundation for new scientific knowledge to be developed; “Any knowledge, no matter how novel, is never a first, totally independent of previous knowledge. It is only a reorganisation, adjustment, correction, or addition with respect to existing knowledge.” (1989, p. 25). Piaget explains how new information is interpreted through modifying and integrating it with previous knowledge in processes known as assimilation and accommodation (Flavell, 1963; Craig, 1972). Here, assimilation involves merging new and existing knowledge structures while accommodation involves manipulating existing knowledge structures to incorporate the merger of new knowledge structures. This emphasis on the role of prior knowledge in constructing new knowledge is echoed in Ausubel's theory of meaningful learning (Ausubel, 1963, 1968). According to Ausubel, for students to engage in learning in a meaningful way as opposed to the rote memorisation of facts, three conditions must be met; (1) the student must have appropriate prior knowledge to which the new knowledge can be connected; (2) the new knowledge must be perceived as relevant to this prior knowledge; (3) the student must choose to make these connections (Ausubel, 1963, 1968).

Specific to the development of scientific knowledge in a teaching and learning context, Driver et al. (1994) set out a precedent for what it means to learn science. Here, learning science is conceptualised as a process that sees an experienced member of the scientific community (teacher) enculturing less experienced members (students) into the particular ways of knowing which are specific to science. These particular ways of knowing pertain to the ideas and practices of the scientific community such as how knowledge claims are generated and validated. The significance of the social context in which students learn science is emphasised by Driver et al. (1994) whereby the teacher assumes responsibility for helping students to make sense of how claims are generated and validated in science.

However while this precedent for learning science emphasised the significance of learning science in a social context, is argued that the construction of new scientific knowledge by scientists cannot equate with students’ acquisition of old scientific knowledge (Osborne, 1996; Ford, 2008). The absence of sufficient ability to rigorously critique scientific claims is claimed to negate the extent to which students learning scientific knowledge can align to the authentic construction of scientific knowledge by scientists (Ford, 2008). A prior and robust foundational understanding of science is crucial for scientists to construct new knowledge upon and without this, it is claimed that students will not be able to engage in scientific reasoning practices effectively (Koslowski, 1996; Osborne et al., 2004; de Arellano and Towns, 2014). Furthermore, since science students accept theories on the authority of the teacher and the text, not because of the evidence, attempts to align learning science and the authentic construction of scientific knowledge may be naïve (Kuhn, 1970; Smith et al., 2000).

Nevertheless, the need for students to understand what scientific knowledge consists of and how it is developed is crucial (Carey and Smith, 1993; Driver et al., 1996; Hogan, 2000; Sandoval, 2005; Duschl, 2008). Student's perceptions of the structure and development of scientific knowledge can be referred to as their epistemology of science. Here, their personal epistemology of science pertains to their beliefs about what scientific knowledge is and how it is developed (Hofer and Pintrich, 1997; Louca et al., 2004). A wealth of research has been devoted to gaining insight into students’ epistemology of science. Students, especially younger ones, can harbour beliefs that scientific knowledge is simple, certain and fact-based (Lederman, 1992; Carey and Smith, 1993; Smith et al., 2000; Sandoval, 2005). Teachers as well as students are shown to have beliefs that scientific knowledge is not tentative (Lederman and O'Malley, 1990; Lederman, 1992). The belief that scientific knowledge is not constructed, but rather directly derived from experiments can be prevalent in younger students, but older students’ beliefs begin to mature in sophistication as they get older to include the construction of models and theories (Driver et al., 1996; Sandoval, 2005). The study by Driver et al. (1996) shows how students can perceive science as a means of addressing questions relating to physical and biological phenomena but not social phenomena and that the purpose of science can be seen to provide solutions to problems rather than providing more powerful explanations.

However, Hogan (2000) makes a distinction between two different ways students can perceive the nature of science. Just as it is important to understand what students believe to be is the nature of science, it is also important to understand their beliefs about what it means to learn science. Here, proximal knowledge of the nature of science refers to “students’ personal understandings, beliefs, and commitments regarding their own science learning and the scientific knowledge they, not scientists, produce and encounter” (Hogan, 2000, p. 51). Proximal knowledge of the nature of science is contrasted by distal knowledge of the nature of science which is declarative knowledge about professional science, including about the nature of scientific knowledge. This provides a useful theoretical lens for this research to explore OCLUE students’ distal knowledge of the nature of science, as their beliefs about the structure and development of scientific knowledge as well as their proximal knowledge of the nature of science, as their beliefs about learning science in the context of OCLUE.

Methodology

Philosophy

In the design of a research study, a researcher must address three philosophical belief systems; the ontological, epistemological and methodological belief systems (Guba and Lincoln, 1994). Since these beliefs are simply accepted on faith, there is no way to establish their ultimate truthfulness (Guba and Lincoln, 1994). The ontology of a study rests within a researcher's perception of the nature of reality and what can be known about it. For example, a study hinging upon a relative ontology subscribes to the belief that reality is experienced in a different way by every person. In the context of this research, a relative ontology would infer the belief that every student has a different conceptualisation of the structure and development of scientific knowledge. In contrary, a realist ontology subscribes to the belief that reality is experienced in the same way by every person. In the context of this research, a realist ontology would infer the belief that all students have the same conceptualisation of the structure and development of scientific knowledge.

However, this study is underpinned by a relativist ontology which seeks to honour the experiences of individual students. This relativist ontology encourages the development of an individualistic research methodology by collecting and analysing data from individuals. Collecting and analysing data from individuals aligns to a subjectivist epistemology whereby epistemology refers to the researchers’ beliefs on the nature of the knowledge that is being pursued by the research. That is, this research believes it is important to collect and analyse data from individual students because every student will have a different conceptualisation of the structure and development of scientific knowledge Therefore, interviews were carried out with each individual student in this research. However, in line with the tenants of constructivist grounded theory research, how the principal researcher collected and analysed the data ultimately underpins a relative ontology and subjective epistemology.

Constructivist grounded theory

Grounded theory is an approach to qualitative research that seeks to construct new theory (Charmaz, 1996; Strauss and Corbin, 1998). When undertaking a grounded theory research study, researchers can either ascribe to, or refute the idea of the existence of an external reality. An external reality to the research and researcher means that the research can develop analytic questions, hypotheses and methodological applications towards learning more about this reality which remains unknown to the researchers (Strauss and Corbin, 1998; Mills et al., 2006). As such, there is an inherent objectivity to this type of grounded theory research. However, if the existence of an external reality is refuted by researchers, a constructivist grounded theory approach may be embraced (Charmaz, 2000). Instead of researchers attempting to learn more about an external reality, constructivist grounded theory sees researchers and participants become co-constructors of their own reality that is unique to them (Charmaz, 2000; Mills et al., 2006). Charmaz's constructivist grounded theory emphasises the role of the researcher in constructing reality based on their interpretations of their participant's stories and experiences. The theory that is generated from constructivist ground theory research reflects both the researcher as well as their interpretations of realty (Hallberg, 2006, p. 146). Therefore, it is important to consider not just the history, background, personal preconceptions, values and beliefs of participants, but also those of the researcher (Cutcliffe, 2000). Therefore, the following paragraph will be used to detail my experiences as a student and researcher.

At the time of this research, I was a post-doctoral research associate with the Cooper Chemistry Education research group at Michigan State University. This group seeks to improve undergraduate chemistry education using an evidence-based best practice model for curricular reform. Prior to traveling to the United States of America to join the Cooper research group, I completed a BSc in science education and a PhD in chemistry graduate student teacher development at a University in Ireland. This immediate research study was carried out three months into my time as post-doctoral research associate. Having travelled from Ireland, I had relatively little experience or insight into the Framework, or how OCLUE had been transformed in line with the Framework. At the time of the interviews, I was developing my understanding of science education and science education transformation in the United States of America. Having graduated from an undergraduate degree programme five years ago, I was relatively close in age and experience to the undergraduate students who participated in this research study. I sought to establish an equal power dynamic between the participants and I during the interviews in the hope that they would not feel inferior or intimidated by me or the interview conditions. I let them choose the time and day they wanted to be interviewed at. I ensured the participants knew their interview responses would have no bearing on their grades and I encouraged them to speak open and honestly. Before the interviews began, I spoke to each participant about how their day was going and how they were feeling in an attempt to make them feel relaxed in my company and in the interview room. Finally, during this research, I made a conscious effort to remain impartial to the principles that guided OCLUE's pedagogical transformation which have been recently published (Cooper et al., 2019). For the purpose of generating theory in relation to how OCLUE students conceptualise the structure and development of scientific knowledge, I did not want to impress OCLUE's pedagogical principles on the outcomes of this research. Rather, I wanted theory to be generated on the students’ own perceptions of what it means to learn in OCLUE.

Organic chemistry, life, the universe and everything

This research was carried out with students enrolled in the first semester of the OCLUE course (Organic chemistry 1, the first course of a two semester sequence). This course is delivered to 300-plus students and consists of two 80 minutes lectures a week and an hour long recitation. OCLUE places on emphasis on providing students with the cognitive tools which span the aforementioned core ideas to construct an explanation for how and why organic reactions occur (Cooper et al., 2019). That is, students are guided to provide causal mechanistic explanations for why organic chemistry reactions proceed. Causal mechanistic reasoning entails accounting for changes in the underlying objects or entities of a phenomena which are at least one scalar level below the phenomenon of interest (Russ et al., 2008; Crandell et al., 2018). Examples of the underlying objects of an organic chemistry mechanism may be the charge distribution within and between the reacting molecules and the electron-rich and electron-deficient sites. After each OCLUE lecture, students are assigned homework that is completed through an online software application, beSocratic (Bryfczynski, 2012; Cooper and Klymkowsky, 2013; Becker, Noyes and Cooper, 2016; Crandell et al., 2018) which the Professor provides formative feedback on at the beginning of each lecture. The beSocratic homework assignments are designed to provide students with opportunities to use ideas discussed in lectures to engage in scientific practices such as constructing causal mechanistic explanations, predictions and/or models.

Participants

Participation in this research was voluntary and all students were informed of their rights prior to their involvement in the research. All data was obtained and handled in accordance with the Institutional Review Board. At the end of the first semester of OCLUE, all students were offered an additional homework credit if they wanted to complete an extra homework assignment or participate in an interview for a research project which was outlined to them in an email. Of the students who expressed their interest to be interviewed, nine students were subsequently invited to be interviewed following a random selection of three students from high, mid and lower performing groups from the OCLUE midterm exams respectively. The students had varying levels of exposure to the CLUE curricula; for Brad, Serena, Katie and Nick, this was their first CLUE course. Sarah and Amy had completed the first semester of CLUE general chemistry. Roger, Jordan and Nancy had completed both semesters of CLUE general chemistry. Both Niall and Monica were invited to be interviewed on a voluntary basis given that they had completed the full CLUE and OCLUE courses. The students were majoring in a diverse range of subjects to include zoology, psychology and biochemistry. No student interviewed was planning to major in chemistry

Data collection

The interviews took place towards the end of the first semester of the OCLUE course and were recorded using a Dictaphone. The interviews took the form of semi-structured interviewing using an interview protocol. This interview protocol began with questions about student's background such as their major, career aspirations, science courses already completed and the science classes they are intending to take. In order to explore OCLUE students’ perceptions of the structure of scientific knowledge, the interview protocol then asked students to discuss whether there would be any differences or similarities in how scientists and non-scientists (those who have not studied science or pursued scientific research) would react to a statistic reported in a news article (Ford, 2008). In order to explore student perceptions of the development of scientific knowledge, students were asked to comment on what scientists do as scientists. Taking these perceptions of the structure and development of scientific knowledge into account, students were then asked to comment on whether they believe they learn science at university in ways which are similar to how they believe scientists do science. Finally, students were asked to account for any similarities or differences in how they learn science in OCLUE compared to how they learn science in other university courses.

Before the interviews began, the principal researcher met with an undergraduate student who had previously completed the OCLUE course to discuss the nature of the questions comprising the interview protocol. The undergraduate student advised the researcher that the questions were appropriately phrased to align to the intended meaning of the questions as set out by the researcher. During the interviews, the researcher did not use words such as ‘construct’, ‘memorise’ or ‘practice’ prior to participants’ first use of these words.

Data analysis

The principal researcher transcribed the interviews and analysed the data in accordance with the procedures and canons of constructivist grounded theory research set out by Charmaz (2014). An open coding process identified a series of codes which served to categorically break down the data. These codes included students’ perceptions of the structure of scientific knowledge, developing scientific knowledge, learning science at university and learning in OCLUE. A process of focused coding then took place. Here, the coding process moved from identifying codes to generating abstract themes which were deemed to be more reflective of the actual experiences and perceptions of the students within each code (Charmaz, 1996, 2000, 2014). The constant comparison method (Glaser and Strauss, 1967) was also incorporated at this stage to incorporate insights from memos written throughout the research process. Theses memos were based on evolving understanding of the data, research process, science education research and policy in the United States of America. Finally, theoretical coding then took place in order to integrate and solidify the analysis in a theoretical structure.

Reliability and validity

Appropriate reliability and validity measures in research are critical because “without rigor, research is worthless, becomes fiction, and loses its utility.” (Morse et al., 2002, p. 14). The role of inter-rater reliability tests and measures in qualitative research is heavily debated (Altheide and Johnson, 1998; Cook, 2011; Noble and Smith, 2015). In an era of blossoming statistical packages and the development of computing systems, the absence of hard numbers and p-values has led to a crisis in confidence in qualitative research (Morse et al., 2002). Establishing consistency of findings through the concept of inter-rater reliability which sees the process of data analysis being conducted by two or more researchers is not entirely necessary in qualitative research (Armstrong et al., 1997). As Morse puts it frankly “no-one takes a second reader to the library to check that indeed he or she is interpreting the original sources correctly, so why does anyone need a reliability check for his or her data?” (Morse, 1994, p. 213). Especially in the context of constructivist grounded theory, this type of research is a fundamental human endeavour that sees both the researcher and their research participants co-constructing a realty together. This article reports on how I, the author, interpreted and reported on the reality that was constructed between myself and the research participants. Adding an additional co-coder to engage in reliability measures will influence my interpretation of the research and therefore diminish the extent to which this research fully aligns to the tenants of constructivist grounded theory.

Nevertheless, reliability and validity remain pertinent in qualitative inquiry (Morse et al., 2002). In the 1980's the terms of reliability and validity where substituted by the concept of trustworthiness to promote and demonstrate rigor in qualitative research (Guba, 1981; Guba and Lincoln, 1981). The methodological strategies associated with trustworthiness in qualitative research include credibility, transferability, dependability and confirmability. However, it is pointed out that while these methodological strategies associated with trustworthiness may be useful to evaluate rigor, they do not ensure rigor (Morse et al., 2002). To address this, Morse et al. (2002) sets out a series of verification strategies to actively attain sufficient and appropriate reliability and validity. Here, verification is the process of checking, confirming, making sure and being certain. The verification strategies used to promote the rigor of this research study include; (i) methodological coherence between the research question and the components of constructivist grounded theory, (ii) appropriate sampling of participants who best represent or have knowledge of the research topic, (iii) concurrent data collection and analysis, (iv) reconfirming new ideas emerging from data in the data that has already been collected and finally, (v) developing theory as both an outcome of the research process and as a template for comparison and further development of the theory.

Limitations

There are limitations to this research. Firstly, it is important to note that this study was carried with just eleven students. Although efforts were made to purposefully select these students based on their performance in exams, their interview responses may not be representative of the entire OCLUE student population. Secondly, the nature of constructivist grounded theory sees both the researcher and the research participants embarking on a journey that co-constructs and reports on what appears to be the reality of what is being investigated by the research (Rapley, 2004; Charmaz, 2014). As a result, the researcher will have an inherent influence on the representation of students’ views. Readers must take into consideration the researchers’ experiences and current capacity as previously discussed in this article when interpreting the findings of this researcher as these have shaped what the researcher saw in the data and how it was reported.

The inverse to the previous point would also encourage readers to take into consideration the assumptions that the students may have harboured during the interviews and how this could have influenced their responses. For example, students may have been aware that behind OCLUE is a team of researchers working to improve how students learn organic chemistry. The students may have been aware that I am a scientist, and chemistry education researcher attempting to achieve this same goal. The students were also receiving homework credit in receipt of their participation in this research. For these reasons and in keeping with good faith, the students may have said the things they felt I wanted to hear. However, instead of perceiving this as a factor that diminishes the credibility and validity of this research, it should be embraced as a means to aid the interpretation of this research.

Thirdly, research can view personal epistemologies as relatively large, coherent, and stable cognitive structures (Louca et al., 2004). Readers should be encouraged to bear in mind that students’ personal epistemologies detailed in this paper are not coherent or stable cognitive structures, rather, that they are constantly evolving as the students grow and mature (Sandoval, 2005).

Finally, as part of this research, students were asked to account for any similarities or differences in how they learn science in OCLUE compared to how they learn science in other university courses. For the purpose of this research, OCLUE is referred to as a transformed course while all other classes are referred to as traditional courses. While these traditional courses have not undergone as much pedagogical transformation as OCLUE, the student responses in regard to such traditional courses cannot be generalised to all traditional courses in different contexts and settings.

Findings

Core category

The core category integrates all of the theory's various aspects (Mills et al., 2006). This core category represents the central phenomenon of the study (Corbin and Strauss, 1990) and combines all of the products of an analysis to explain “what this research is all about” (Strauss and Corbin, 1998, p. 146). In this case, the core category of this research study is how students in a transformed organic chemistry course conceptualise the structure and development of scientific knowledge.

Students in this research demonstrated an awareness that behind scientific claims is important information that determines the validity of the claim. Having the ability to perceive and interrogate the rigor of this claim was thought to distinguish scientists from non-scientists. This belief also transcended into a University setting whereby it was believed that students who do not study science are more naïve and credulous than science students. Students noted that a distinguishing feature of OCLUE was the need to ‘work behind the answer’. This meant that students needed to provide a reason for answers and they needed to interrogate their prior knowledge in order to digest new information. They perceived the hierarchical structure of knowledge and if they did not understand foundational concepts or understandings, this would inhibit the development of their knowledge.

Students noted that the development of scientific knowledge is rarely straight-forward or pre-determined. Instead, it was believed that scientists needed to piece together what they know in seemingly random ways in order to solve science puzzles. Students explained that scientists and doctors cannot just rely on memorising all there is to know in science. Instead, they need to practice what they know. In the context of OCLUE, students explained that memorising information ahead of OCLUE exams was insufficient. Instead, they had to synthesise and interrogate their prior understanding to figure out new problems in OCLUE exams.

It will become apparent throughout the discussion of students’ responses that OCLUE contributed to the development of a more sophisticated proximal knowledge of the structure and development of scientific knowledge (Hogan, 2000). This will transpire as students emphasise the importance of perceiving, interrogating and refining their prior knowledge to build up their understanding and the insufficiency of memorisation techniques when learning organic chemistry in OCLUE.

Structure of scientific knowledge

This research sought to gain insight into how students perceived the structure of scientific knowledge by asking them whether there would be any differences or similarities in how scientists and non-scientists would react to a scientific claim, such as a statistic reported in a news article. This line of inquiry stemmed from the work of Ford (2008) who claims that “a proper understanding of a scientific idea requires that one also know something about the architecture of that knowledge, that is, how it is constructed” (2008, p. 404). Students were aware of the significance of the information that is used to build a claim in science. All of the students in this study believed that having the ability to identify and critique this information served to distinguish scientists from non-scientists, supporting the contentions of Ford (2008);

 

“I feel like sometimes scientists are like, ok, show me not just the statistic, show me the data behind this, show me the study, show me all of the background information whereas sometimes people who like don't do research and are not involved in that stuff just take it as it is or either that they don't understand the statistic.” (Monica)

 

Non-scientists, or as Amy referred to them as ‘normal people’, were depicted as being more credulous and naïve. Amy believed that those who did not do science would either not understand the statistic or either, they would not care enough to ask more questions of the information behind the claim;

 

“Like, a normal person could take it as fact, but a science person would question that sample size or something like that, and who did the test, say there could be errors in it.” (Amy)

 

The tendency for scientists to exude greater scepticism in light of statements or claims was also believed to extend to students who study science at University;

 

“So students that are not in science based lectures, I would say they just kind of take things as they come and accept facts. When it comes to science, you really got to get the little parts before you can get everything else. And that would be like, ok, so, a history analogy would be, the union army won the battle of Bunker Hill, but!, someone not in a science based lecture would say, ok, yeah, they won that, but, a scientist would want to know how they got to that point and all the factors that led up to it and if they could have lost.” (Roger)

 

Roger assumed here that history students would not be as curious as science students because science students would demand to know more about how a particular battle in history was won. Students can have a beneficent view of scientists as they are perceived to be responsible and capable in addressing important problems which are of relevance to society (Driver et al., 1996). The science students in this study tended to elevate the members of the science community because scientists were believed to have the ability to think deeper and critique more rigorously than those who do not do science. However, the lack of opportunity to engage in this way of thinking while learning science at University was noted to restrict the extent to which Roger felt he was learning science in a scientific way at University;

 

“What I have been doing lately a lot in biology is that they will give us an answer, like, well, ATP drives the sodium-phosphate pump in your cells, but, why does it do that? So, like, in class, that question was asked and the answer was ATP drives it because a phosphate breaks off, but it goes deeper than that, you got to try and understand all that little stuff first” (Roger)

 

Here, Roger recognised the need to understand why phenomena occur in science. The processes of describing what and explaining why are different, and students can distinguish between these processes (Crandell et al., 2018). A prominent aim of OCLUE is for students to therefore “go beyond the idea that a reaction occurs (e.g., generates a product), and beyond how a reaction occurs (i.e., draw a mechanism), to construct a causal mechanistic explanation in order to explain why a reaction occurs.” (Cooper et al., 2019, p. 1861). This aim transpired through Katie's account for what makes learning in OCLUE different from learning in other courses;

 

“Yeah, like [in OCLUE] we learn what a good nucleophile is, and like, what makes a good leaving group, and you know, every little step that goes into what makes it good, and we learnt the concepts. I feel like in my other past classes, we learn like, ok, this is a good nucleophile, you don't need to know why or anything.” (Katie)

 

While Katie noted OCLUE's intention to help students account for why phenomena occur, Roger explained how OCLUE requires students to interrogate the information ‘behind the answer’;

 

“…you have to really do the work behind the answer because, [The Professor] will put stuff on the board and it's like, 'where did that come from? ', but [The Professor] explained it and it makes sense but you have to back-track a lot so there's a lot of back-track… we just keeping building.” (Roger)

 

In similar fashion, Amy described how the BeSocratic homework assignments provided her with an opportunity to interrogate and build up her understanding.

 

“I would say it's interesting in this class because I will have done problems that are like solved on BeSocratic the night before … I go to class the next day, we go through that and kind of prove things wrong, like in my head I'm crossing off boxes, like, ok you didn't do that right, why did you think that way?, and then we're learning because we'll go over the homework, which I really enjoy because it is very comprehensive, like, instead of just opening up a lecture and saying word junk, like just reciting off a lecture or something like that, I am going over my thought processes, then you start learning things, so you build it up.” (Amy)

 

Nick explained how OCLUE facilitated the use of his prior knowledge to understand new ideas;

 

“I figure [OCLUE has] taught me how to like really go back and you got to look at previous stuff and apply it to what you are learning now because if I am going to try and memorise what I want to learn now, it's never going to work, I am never going to be able to looks at something in orgo and just memorise it, I got to look back at what I know and apply it to what I am trying to figure out.” (Nick)

 

The extent to which students described learning in OCLUE to involve the manipulation of their prior knowledge was notable. Students constantly referred to back-tracking and building up processes in order to account for why phenomena occur in science. These processes resonate with Piaget's tenants of constructivism which include assimilation and accommodation (Flavell, 1963; Craig, 1972; Piaget and Garcia, 1989). OCLUE's perceived pedagogic aim to entail helping students to construct their understanding was further supported by Amy;

 

“I think that reflection would be a huge part of it and then you have to do independent study to make all those pre-conceived notions of what you think is right and then you have to fact-check them and make sure they are right to build on top of itself because if you have one foundation layer poorly set, it would off-set everything that you learn afterwards.” (Amy)

 

From these responses, it is apparent that OCLUE students conceptualised a hierarchical structure of scientific knowledge whereby behind claims and answers in science is important information that determines the validity of the claim or answer. Being adept in utilising this information was important to students as it provided them with the opportunity to account for why organic chemistry phenomena occur. OCLUE provided students with an opportunity to build up their understanding by establishing a robust foundation of prior knowledge that could be used to further their developing understanding of organic chemistry.

Developing scientific knowledge

Advancing the state of scientific knowledge is often typically associated with equivocal terms such as critical thinking, problem solving and inquiry (Hunter et al., 2007; Brownell et al., 2015). The nature of science is elaborated in sophisticated models such as the Family Resemblance Approach which conceptualises science as a shared and distinctive set of scientific practices, methodologies, aims and values, social norms (Erduran and Dagher, 2014; Dagher and Erduran, 2016). Lederman et al. (2002) propose seven aspects of the nature of science whereby (a) scientific knowledge is tentative, (b) is partially subjective (i.e., theory laden), (c) relies on an empirical basis, (d) is creative, (e) is socially and culturally embedded, (f) is based upon observations and inferences, and (g) theories and laws are different forms of scientific knowledge. However students in this study did not use equivocal terms or depict nebulous conceptualisations of science. The students portrayed the work of scientists as a mysterious endeavour. Making a contribution to the state of scientific knowledge was acknowledged to be rarely straight-forward or pre-determined, necessitating trial, error, success and failure.

Jordan portrayed the process of doing science akin to solving a puzzle. The method to solving this puzzle could not be pre-determined. What was required instead is to piece together the various pieces of the puzzle in seemingly trial-and-error ways in order to solve the puzzle;

 

“… usually when I think of scientists it's a lot of like trial and error through experiment and trying to find the right pieces to solve whatever they want to figure out” (Jordan)

 

This process of piecing together information in previously undetermined ways was noted to be necessary in the context of learning science. This process was juxtaposed against the process of memorising information. Amy claimed that memorising information will afford students information that they can ‘spit out whenever they need it’ without the opportunity to ‘get it’ conceptually. The alternative of this was to piece together information in order to develop a conceptualisation of the information at hand;

 

“Studying wise, [In other courses] you have to go back over everything because you haven't like conceptualised it, you have just been given it, you haven't put stuff together, you haven't pieced it together in your head, and then, that's almost more like the memorise what they have said and regurgitate it, because you don't get it conceptually, you just know this information, you have it to use or spit out whenever you need it” (Amy)

 

There is an assumption that organic chemistry involves memorising a considerable volume of content and recognising and memorising patterns (Cooper et al., 2019). However, a distinguishing feature of learning science in OCLUE was not having to memorise course material before OCLUE exams. Instead of memorising, Brad and Monica described thought processes that involved manipulating what they know in various ways in order to navigate their way through OCLUE exam questions;

 

“We had [a traditional] organic chemistry unit and it was not so much knowing the mechanisms as like memorising what happens and I just remember studying that for like so long, just memorising, this goes here, didn't really care about why, and like, switching that hydrogen in a reaction or whatever and in this [OCLUE] class, I feel like I have a process, like you look at the charges, see what would react or where things would go and that's like, you work through it to get the result so that's why I feel like I don't have to memorise it as much, it's like a process that I go through for each problem.” (Brad)

 

As opposed to cramming information before her traditional chemistry exam, Monica noted that preparing for her OCLUE exams involved reminding herself of the main concepts which she could rely on to ‘reason’ through problems in the exam.

 

When studying for OCLUE; “I would just have to remind myself of the concepts and there's no like, hours and hours of studying, it was more like, you are actually learning the stuff over time so when it came to the test, it was like, ok, I can reason through these problems, like this stuff makes sense, [In the traditional course] I would have not paid attention in class for weeks, literally weeks and then, I would come to the test and it would be three days ahead, four days, and I would just literally cram for four days and just take the test and I would have to memorise so many different reactions but it didn't mean anything to me, I didn't care, it literally had no meaning.” (Monica)

 

What makes these assertions by Brad and Monica similar is that they both describe similar thought processes that were juxtaposed against memorising information when preparing for OCLUE exams. Both descriptions involve piecing together what they know as opposed to memorising information. This reflects the development of epistemic heuristics which are “patterned ways of engaging in knowledge-building activity that reflect underlying, implicit understandings about the disciplinary knowledge and knowledge-building practices that are expected and appropriate in context” (Krist et al., 2019, p. 168). Both Brad and Monica perceived the necessary intellectual resources required to reason through OCLUE problems and secondly, how they needed to manipulate these intellectual resources to reason successfully through OCLUE problems (DiSessa, 1993; Hammer and Elby, 2003).

Amy gave another example of how learning in OCLUE could be differentiated due to the insufficiency of memorising content when preparing for OCLUE exams. In lieu of memorising content, she felt she needed to place more emphasis on practicing organic chemistry;

 

[In other courses] “I would probably just make notecards but I couldn't make notecards for OCLUE because you have to think and practice it, that's why I feel like we practice more. Like doing practice rounds more than just memorising anything.” (Nancy)

 

Practicing science was more closely associated with thinking about content as opposed to memorising content in the absence of considerable thought. Nancy went on to explain why she believed practicing science in this manner more closely resonates to the work of a scientist;

 

“…scientists they have to actually practice what they learn. They can't just memorise everything and know everything.” (Nancy)

 

The precedence and value of learning to understand content, rather than memorise content was also highlighted by Brad;

 

“I mean, a lot of people are pre-med here and I would not want my doctor to like, have memorised, and not understand how things work because, everybody is different, you need to know the processes like, know how it all works.” (Brad)

 

Students also acknowledged the need for scientists to be creative in their endeavours to advance scientific knowledge. According to Amy, they have to think differently to other scientists;

 

“…maybe there's a sense of creativity in there that they have to try things that others haven't, to think outside the box, try things based on their knowledge” (Amy)

 

In similar light, Jordon pointed out that he thought OCLUE afforded him the autonomy to think for himself prior to being told how to do it;

 

“I like the CLUE lectures because you do it on your own. You discover if for yourself instead of ‘here, this is what you need to do’. We are given an opportunity to try to learn it on our own and if we can't get it on our own, we are told after, ‘right, here's how you do it’. In most other lectures, it's like, ‘here's how you do it, try it’ and then they tell you, ‘alright, you did it wrong or you got it right.” (Jordan)

 

However, immersing students in an environment whereby they have to construct, reason and explain in ways not previously considered or memorised may contribute other implications to learning experiences. New pedagogical approaches, especially those that encourage independent and active learning can cause concern from students if they feel their grades could be in jeopardy (Woods, 1996). Richard noted how emotions can run high in OCLUE

 

“…probably OCLUE is one of the one's that I have been most, like, verbally agitated! And just like emotionally agitated by the content. Not because it was like awful or something but because I cared enough to be upset…when you have that emotion, I guess, with it, it just, it just kind of shows you how engaged you are or how much you do actually care and how you are thinking about it at a deeper level.” (Richard)

 

Although Richard perceived his emotional agitation in a positive light by using it to indicate his engagement and how much he cares about what he was learning in OCLUE, other students may not deal with a heightened emotional response so positively. Memorising content for high stakes exams may be an attractive approach to learning science for students as it affords them a sense of control over what grade they get. However, learning science in ways which do not emphasise the need to extensively memorise, rather, by having to use what students know in ways not previously considered or memorised may exacerbate students’ sense of fear. Alluding to the profound power of grades in determining the futures of students, Serena pointed out that fearing the potential of thinking incorrectly could pose considerable consequences for students;

 

“I think [Students] are afraid to think because they don't want to think wrong, I don't think they want to be wrong… your grade is your future and if you don't pass, that's kind of a detriment towards your future” (Serena)

 

Yet however, there will always be students who just do not care about how they learn science, they are just interested in getting to the finish line as Monica points out;

 

“…there are people who don't care how it's taught, they just want to be done with it, they just don't care.” (Monica).

Implications for teaching

This research may provide implications for how science is taught at university. Firstly, science is not a straight-forward or pre-determined process, and learning science should not be either. In this study, OCLUE students emphasised that memorising for science exams is not reflective of any true scientific endeavour. Instead of memorising, they acknowledged the precedence of being afforded the space and opportunity to be creative with what they know. If we are to be responsible of producing graduates who are sufficiently capable of pursuing and progressing scientific knowledge, then they must be afforded the opportunity and autonomy to use what they know creatively. This requires instructors to be mindful of their own personal epistemology of science and how this should transpire through their pedagogy, to decide on what students will need to know and be able to do with their knowledge, to afford students the opportunity and autonomy to use what they know creatively, and finally, to be conscious of that fact that pedagogical changes, especially those that limit students’ control over their grade by minimising the extent to which memorisation techniques suffice, will possibly incur emotional responses within students which will need to be regulated and accommodated accordingly.

Secondly, it comes as a recommendation to address the development (and perhaps, the assessment) of students’ epistemology of chemistry and chemistry education, that is, what students believe is the nature of chemistry and chemistry education. Although OCLUE contributed to students developing a more sophisticated conceptualisation of what it means to learn science, it did so on an implicit basis. The goal of OCLUE was not to advance students’ personal epistemology of science but rather than to progress students understanding of core ideas in organic chemistry through the use of scientific practices. Nevertheless, through having to construct and synthesise their understanding of organic chemistry as opposed to memorise facts, OCLUE students were afforded opportunities to learn organic chemistry in a more scientific way. Advancing epistemic beliefs should be a goal of science education because these beliefs are subject to change (Hammer and Elby, 2003; Louca et al., 2004; Schwartz et al., 2004) and more sophisticated epistemologies of science can lead to better learning outcomes and experiences (Carey and Smith, 1993; Driver et al., 1996; Hogan, 2000; Sandoval, 2005; Duschl, 2008). The primary goal of science education has long been to develop students understanding of science concepts, with epistemic and social learning goals remaining as secondary goals (Duschl, 2008). Any advancements to students’ views on the nature of science is thought to occur as a by-product of engaging in science related activities (Abd-El-Khalick and Lederman, 2000). However, it is argued that conceptual goals should not separate from epistemic and social goals, rather, that each should reinforce and mutually establish each other (Duschl, 2008). Furthermore, it is also argued that advancing students’ epistemic beliefs is a cognitive learning outcome (Abd-El-Khalick and Lederman, 2000).

Implications for research

This research may also offer directions for future research. Firstly, the insights generated from this grounded theory approach would not have been obtained using a quantitative research approach. The efficacy of new chemistry curricula in improving learning are often evaluated quantitatively (Flynn and Biggs, 2011; Cooper et al., 2012; Flynn, 2015; Williams et al., 2015; Underwood et al., 2016; Crandell et al., 2018) and the use of qualitative methods to investigate improvements in learning, or science epistemologies for that matter are more seldom.

Secondly, this research did not consider whether there exists a relationship between performance and level of sophistication of students views on the structure and development of scientific knowledge. While literature suggests that more advanced epistemologies of science contributes to better learning (Dunbar, 1993; Schauble et al., 1995; Sandoval, 2005), future research could investigate the relationship between performance and students’ views on the structure and development of scientific knowledge in chemistry.

Finally, future research could address the advancement of students’ conceptualisations of the structure and development of scientific knowledge. It is assumed that seeking to achieve such is an affective goal, and that it would be an inevitable by-product of engaging in science related activities (Abd-El-Khalick and Lederman, 2000). Nevertheless, it is argued that students understanding of the nature of science is a cognitive learning outcome (Abd-El-Khalick and Lederman, 2000) and a profound science learning outcome at that (Carey and Smith, 1993; Driver et al., 1996; Hogan, 2000; Sandoval, 2005; Duschl, 2008).

Conclusion

This study reports on how OCLUE students conceptualise the structure and development of scientific knowledge. OCLUE students conceptualised a hierarchical structure of scientific knowledge whereby behind claims and answers in science is important information that determines the validity of the claim or answer. Being adept in utilising this information was important to students in OCLUE as it provided them with the opportunity to account for why phenomena occur in organic chemistry.

Students explained that the process of developing scientific knowledge is rarely straight-forward or pre-determined. Instead, it was believed that scientists needed to piece together what they know in seemingly random ways in order to solve science puzzles. In the context of OCLUE, students explained that memorising information ahead of OCLUE exams was insufficient. Instead, they had to synthesise and interrogate their prior understanding to figure out new problems in OCLUE exams. Students attributed the efficacy of OCLUE's pedagogy to helping them to engage in constructivist thinking processes that involved interrogating and applying their prior knowledge.

This contributes to the understanding that OCLUE has set out a precedent organic chemistry course that can foster a more scientific way of learning science that contrasts students’ engagement in considerably arduous memorisation techniques.

Conflicts of interest

There are no conflicts to declare.

Acknowledgements

The author wishes to sincerely thank Professor Melanie M. Cooper for her exceptional expertise, guidance and opportunity to pursue this research. Thanks are also extended to those who participated in this research, and of course, the members of the Cooper Research Group for their support and encouragement from across the Atlantic.

References

  1. Abd-El-Khalick F. and Lederman N. G., (2000), Improving science teachers' conceptions of nature of science: a critical review of the literature, Int. J. Sci. Educ., 22(7), 665–701.
  2. Altheide D. L. and Johnson J. M., (1998), Criteria for assessing interpretive validity in qualitative research, in Denzin N. K. and Lincoln Y. S. (ed.), Collecting and interpreting qualitative materials, Thousand Oaks, CA: Sage, pp. 283–312.
  3. Armstrong D., Gosling A., Weinman J. and Marteau T., (1997), The place of inter-rater reliability in qualitative research: an empirical study, Sociology, 31(3), 597–606.
  4. Ausubel D., (1963), The Psychology of Meaningful Verbal Learning, New York: Grune & Stratton.
  5. Ausubel D., (1968), Educational Psychology: A Cognitive View, New York: Holt, Rinehart & Winston.
  6. Becker N., Noyes K. and Cooper M., (2016), Characterizing students’ mechanistic reasoning about London dispersion forces, J. Chem. Educ., 93(10), 1713–1724.
  7. Brownell S. E., Hekmat-Scafe D. S., Singla V., Chandler Seawell P., Conklin Imam J. F., Eddy S. L. and Cyert M. S., (2015), A high-enrollment course-based undergraduate research experience improves student conceptions of scientific thinking and ability to interpret data, CBE-Life Sci. Educ., 14(2), ar21.
  8. Bryfczynski S., (2012), BeSocratic: BeSocratic: An Intelligent Tutoring System for the Recognition, Evaluation, and Analysis of Free-Form Student Input, PhD Dissertation, Clemson, SC: Clemson University.
  9. Carey S. and Smith C., (1993), On Understanding the Nature of Scientific Knowledge, Educ. Psychol., 28(3), 235–251.
  10. Charmaz K., (1996), The Search for Meanings – Grounded Theory, in Smith J. A., R. Harre and L. Van Langenhove (ed.), Rethinking Methods in Psychology, London: Sage Publications.
  11. Charmaz K., (2000), Grounded theory: objectivist and constructivist methods, Handbook Qual. Res., 2, 509–535.
  12. Charmaz K., (2014), Constructing Grounded Theory, London: Sage Publications Ltd, 2nd edn.
  13. Cook K. E., (2011), Reliability assessments in qualitative health promotion research, Health Promot. Int., 27(1), 90–101.
  14. Cooper M., (2010), The case for reform of the undergraduate general chemistry curriculum, J. Chem. Educ., 87(3), 231–232.
  15. Cooper M., (2016), It Is Time To Say What We Mean, J. Chem. Educ., 93(5), 799–800.
  16. Cooper M. and Klymkowsky M., (2013), Chemistry, Life, the Universe, and Everything: A New Approach to General Chemistry, and a Model for Curriculum Reform, J. Chem. Educ., 90(9), 1116–1122.
  17. Cooper M., Underwood S., Hilley C. and Klymkowsky M., (2012), Development and assessment of a molecular structure and properties learning progression, J. Chem. Educ., 89(11), 1351–1357.
  18. Cooper M., Stowe R., Crandell O. and Klymkowsky M., (2019), Organic Chemistry, Life, the Universe and Everything (OCLUE): A Transformed Organic Chemistry Curriculum, J. Chem. Educ., 96(9), 1858–1872.
  19. Corbin J. M. and Strauss A., (1990), Grounded theory research: procedures, canons, and evaluative criteria, Qual. Sociol., 13(1), 3–21.
  20. Craig B. S., (1972), The philosophy of Jean Piaget and its usefulness to teachers of chemistry, J. Chem. Educ., 49(12), 807.
  21. Crandell O. M., Kouyoumdjian H., Underwood S. M. and Cooper M. M., (2018), Reasoning about Reactions in Organic Chemistry: Starting It in General Chemistry, J. Chem. Educ., 96(2), 213–226.
  22. Cutcliffe J. R., (2000), Methodological Issues in Grounded Theory, J. Adv. Nurs., 31(6), 1476–1484.
  23. Dagher Z. R. and Erduran S., (2016), Reconceptualizing the nature of science for science education, Sci. Educ., 25(1–2), 147–164.
  24. de Arellano D. C.-R. and Towns M. H., (2014), Students' understanding of alkyl halide reactions in undergraduate organic chemistry, Chem. Educ. Res. Pract., 15(4), 501–515.
  25. DiSessa A. A., (1993), Toward an Epistemology of Physics, Cognit. Instruct., 10(2–3), 105–225.
  26. Driver R., Asoko H., Leach J., Scott P. and Mortimer E., (1994), Constructing scientific knowledge in the classroom, Educ. Res., 23(7), 5–12.
  27. Driver R., Leach J., Millar R. and Scott P., (1996), Young People's Images of Science, Buckingham, Philadelphia: Over University Press.
  28. Dunbar K., (1993), Concept Discovery in a Scientific Domain, Cognit. Sci., 17(3), 397–434.
  29. Duschl R., (2008), Science education in three-part harmony: balancing conceptual, epistemic, and social learning goals, Rev. Res. Educ., 32(1), 268–291.
  30. Erduran S. and Dagher Z. R., (2014), Reconceptualizing Nature of Science for Science Education, in Reconceptualizing the Nature of Science for Science Education, Springer Netherlands, pp. 1–18.
  31. Flavell J. H., (1963), The Developmental Psychology of Jean Piaget, New York: Van Nostrand.
  32. Flynn A. B., (2015), Structure and evaluation of flipped chemistry courses: organic & spectroscopy, large and small, first to third year, English and French, Chem. Educ. Res. Pract., 16(2), 198–211.
  33. Flynn A. B. and Biggs R., (2011), The development and implementation of a problem-based learning format in a fourth-year undergraduate synthetic organic and medicinal chemistry laboratory course, J. Chem. Educ., 89(1), 52–57.
  34. Ford M., (2008), Disciplinary Authority and Accountability in Scientific Practice and Learning, Sci. Educ., 92(3), 404–423.
  35. Glaser B. and Strauss A., (1967), The Discovery of Grounded Theory: Strategies for Qualitative Research, Hawthorne, New York: Aldine.
  36. Guba E. G., (1981), Criteria for assessing the trustworthiness of naturalistic inquiries, Educ. Commun. Technol. J., 29(2), 75–91.
  37. Guba E. G. and Lincoln Y. S., (1981), Effective evaluation: Improving the usefulness of evaluation results through responsive and naturalistic approaches, San Francisco, CA: Jossey-Bass.
  38. Guba E. G. and Lincoln Y. S., (1994), Competing Paradigms in Qualitative Research, Handbook Qual. Res., 2, 163–194.
  39. Hallberg L. R., (2006), The “core category” of grounded theory: making constant comparisons, Int. J. Qual. Stud. Health Well-being, 1(3), 141–148.
  40. Hammer D. and Elby A., (2003), Tapping Epistemological Resources for Learning Physics, J. Learn. Sci., 12(1), 53–90.
  41. Havighurst R. J., (1929), Reform in the chemistry curriculum, J. Chem. Educ., 6(6), 1126.
  42. Hofer B. K. and Pintrich P. R., (1997), The development of epistemological theories: beliefs about knowledge and knowing and their relation to learning, Rev. Educ. Res., 67(1), 88–140.
  43. Hogan K., (2000), Exploring a process view of students' knowledge about the nature of science, Sci. Educ., 84(1), 51–70.
  44. Hunter A. B., Laursen S. L. and Seymour E., (2007), Becoming a scientist: the role of undergraduate research in students' cognitive, personal, and professional development, Sci. Educ., 91(1), 36–74.
  45. Koslowski B., (1996), Theory and evidence: the development of scientific reasoning, MIT Press.
  46. Krist C., Schwarz C. V. and Reiser B. J., (2019), Identifying essential epistemic heuristics for guiding mechanistic reasoning in science learning, J. Learn. Sci., 28(2), 160–205.
  47. Kuhn T. S., (1970), The Structure of Scientific Revolutions, Chicago: University of Chicago Press, 2nd edn.
  48. Kuhn T., (2012), The Structure of Scientific Revolutions, Chicago: The University of Chicago Press, 4th edn.
  49. Lederman N. G., (1992), Students' and teachers' conceptions of the nature of science: a review of the research, J. Res. Sci. Teach., 29(4), 331–359.
  50. Lederman N. G. and O'Malley M., (1990), Students' perceptions of tentativeness in science: development, use, and sources of change, Sci. Educ., 74(2), 225–239.
  51. Lederman N., Abd-El-Khalick F., Bell R. L. and Schwartz R. S., (2002), Views of Nature of Science Questionnaire: Toward Valid and Meaningful Assessment of Learners' Conceptions of Nature of Science, J. Res. Sci. Teach., 39(6), 497–521.
  52. Lloyd B. W. and Spencer J. N., (1994), The Forum: New Directions for General Chemistry: Recommendations of the Task Force on the General Chemistry Curriculum, J. Chem. Educ., 71(3), 206 DOI:10.1021/ed071p206.
  53. Louca L., Elby A., Hammer D. and Kagey T., (2004), Epistemological Resources: Applying A New Epistemological Framework to Science Instruction, Educ. Psychol., 39(1), 57–68.
  54. Mills J., Bonner A. and Francis K., (2006), The development of constructivist grounded theory, Int. J. Qual. Methods, 5(1), 25–35.
  55. Morse J. M., (1994), Designing Funded Qualitative Research, in Denzin N. K. and Lincoln Y. S. (ed.), Handbook of qualitative research, Thousand Oaks, CA: Sage Publications, Inc, pp. 220–235.
  56. Morse J., Barrett M., Mayan M., Olson K. and Spiers J., (2002), Verification strategies for establishing reliability and validity in qualitative research, Int. J. Qual. Methods, 1(2), 13–22.
  57. National Research Council, (1999), Transforming undergraduate education in science, mathematics, engineering, and technology, National Academies Press.
  58. National Research Council, (2012), A Framework for K-12 Science Education: Practices, Crosscutting Concepts, and Core Ideas, Washington, DC: The National Academies Press.
  59. Noble H. and Smith J., (2015), Issues of validity and reliability in qualitative research, Evid. Nurs., 18(2), 34–35.
  60. Olson S. and Riordan D. G., (2012), Engage to Excel: Producing One Million Additional College Graduates with Degrees in Science, Technology, Engineering, and Mathematics, Report to the President. Executive Office of the President.
  61. Osborne J., (1996), Beyond Constructivism, Sci. Educ., 80(1), 53–82.
  62. Osborne J., Erduran S. and Simon S., (2004), Enhancing the quality of argumentation in school science, J. Res. Sci. Teach., 41(10), 994–1020.
  63. Otero V. K. and Meltzer D. E., (2016), 100 years of attempts to transform physics education, Phys. Teach., 54(9), 523–527.
  64. Piaget J. and Garcia R., (1989), Psychogenesis and the History of Science, New York: Columbia University Press.
  65. Piaget J., Brown T. and Thampy K., (1985), The Equilibration of Cognitive Structures: The Central Problem of Intellectual Development, Chicago: University of Chicago Press.
  66. Rapley T., (2004), Interviews, in Seale C., Gobo G., Gubrium J. F. and Silverman D. (ed.), Qualitative Research Practice, London: Sage Publications, pp. 15–33.
  67. Russ R. S., Scherr R. E., Hammer D. and Mikeska J., (2008), Recognizing mechanistic reasoning in student scientific inquiry: a framework for discourse analysis developed from philosophy of science, Sci. Educ., 92(3), 499–525.
  68. Sandoval W. A., (2005), Understanding students' practical epistemologies and their influence on learning through inquiry, Sci. Educ., 89(4), 634–656.
  69. Schauble L., Glaser R., Duschl R. A., Schulze S. and John J., (1995), Students' understanding of the objectives and procedures of experimentation in the science classroom, J. Learn. Sci., 4(2), 131–166.
  70. Schwartz R. S., Lederman N. G. and Crawford B. A., (2004), Developing views of nature of science in an authentic context: an explicit approach to bridging the gap between nature of science and scientific inquiry, Sci. Educ., 88(4), 610–645.
  71. Shapiro H., Østergård S. and Hougard K., (2015), Does the EU need more STEM graduates? Luxembourg: Publications Office of the European Union.
  72. Smith C. L., Maclin D., Houghton C. and Hennessey M. G., (2000), Sixth-Grade Students' Epistemologies of Science: The Impact of School Science Experiences on Epistemological Development, Cognit. Instruct., 18(3), 349–422.
  73. Strauss A. and Corbin J., (1998), Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory.
  74. Tsou J. Y., (2006), Genetic epistemology and Piaget's philosophy of science: Piaget vs. Kuhn on scientific progress, Theory Psychol., 16(2), 203–224.
  75. Underwood S., Reyes-Gastelum D. and Cooper M., (2016), When do students recognize relationships between molecular structure and properties? A longitudinal comparison of the impact of traditional and transformed curricula, Chem. Educ. Res. Pract., 17(2), 365–380.
  76. Williams L. C., Underwood S. M., Klymkowsky M. W. and Cooper M. M., (2015), Are Noncovalent Interactions an Achilles Heel in Chemistry Education? A Comparison of Instructional Approaches, J. Chem. Educ., 92(12), 1979–1987.
  77. Woods D. R., (1996), Problem-based learning for large classes in chemical engineering, New directions for teaching and learning, 1996(68), 91–99.
This journal is © The Royal Society of Chemistry 2020