James
M. Nyachwaya
*a and
Merry
Gillaspie
b
aDepartment of Chemistry and Biochemistry, and School of Education, North Dakota State University, P.O Box 6050, Fargo, ND 58108, USA. E-mail: james.nyachwaya@ndsu.edu
bDepartment of Chemistry, Wartburg College, 100 Wartburg Blvd, Waverly, IA 50677
First published on 29th September 2015
The goals of this study were (1) determine the prevalence of various features of representations in five general chemistry textbooks used in the United States, and (2) use cognitive load theory to draw implications of the various features of analyzed representations. We adapted the Graphical Analysis Protocol (GAP) (Slough et al., 2010) to look at the type of representations used, the function of each representation, the physical integration of representations with associated text, the presence and nature of captions and labels, the indexing of representations, and the number of representations requiring conceptual integration on a given page. Results indicate that on average, in all five textbooks each page had at least four representations. Most representations served a ‘representational’ function, but a number functioned as decorative representations. Most representations were directly integrated with text, but some of the remaining representations were separated by a whole page from associated text. While many pages had an average of two representations that required conceptual integration with text or other representations, some pages had as many as six representations requiring integration. While using textbooks, learners can experience intrinsic, germane or extraneous cognitive load (Sweller, 1994). Our findings indicate that there are various features of representations that could help reduce intrinsic or extraneous cognitive load. However, we also found prevalent features of representations that imply high intrinsic cognitive load or are likely to lead to extraneous cognitive load. Implications for textbook authors and editors, textbook selection, instruction, and science teacher preparation are discussed.
Learners pay the most attention to text because it is the mode that more directly presents information, and it is therefore more accessible to learners (Rapport and Ashkenazi, 2008). However, research by Mayer (2001) showed that when information is presented via text only students have a hard time remembering what they read; transferring knowledge from text only sources, especially into problem solving situations, was also difficult. On the other hand, when multimedia presentations are used, learners performed better on problem solving (Mayer, 2001). Other research has found that when learners were presented with only text it was more difficult for them to comprehend material compared to when the text was paired with a representation (Carney and Levin, 2002; Gyselinck et al., 2008). Indeed, communicating scientific information to learners through multiple representations is known to enhance conceptual understanding (Kozma, 2003; Seufert, 2003; Ainsworth, 2006). Multiple representations help organize information, improve comprehension, and support the remembering of information (Carney and Levin, 2002; Butcher, 2006; Homer and Plass, 2010). Combining multiple representations from different formats has been found to be beneficial to learners (Mayer, 1997; Kintsch, 2004; Sadoski and Paivio, 2007; Schnotz, 2008).
Thus, the process of integrating representations with text or other representations is part of an active learning process (Mayer, 1999, 2001). Text is initially processed in the visual subsystem of working memory, the same place where visual representations are processed. Text and representations therefore compete for the learner's attention, decreasing the number of representations and text elements that one can pay attention to at a given time (Mayer et al., 2001). In addition, the mere presence of a representation in a textbook does not mean that it will necessarily communicate and facilitate the intended conceptual understanding of content (Gkitzia et al., 2011). In light of the research that highlights both the benefits and potential pitfalls of representations, this study has two aims: (1) analyzing features of representations in general chemistry textbooks (their nature and characteristics), and (2) interpreting the features through the lens of the cognitive load theory. The study is guided by the following research questions:
1. What is the average number of representations per page?
2. What function do representations serve in General Chemistry textbooks?
3. To what extent are representations physically integrated with the running text?
4. To what extent are representations and mathematical equations indexed within the running text?
5. (a) What proportion of representations have captions?
(b) What proportion of representations have labels?
6. (a) To what extent do representations require conceptual integration with the text and each other?
(b) On average, how many ‘interacting groups’ of representations are on a page?
These questions are significant because, besides text, representations are the most prominent feature in general chemistry textbooks. It is therefore beneficial to examine features of representations in order to get a sense of their utility as part of chemistry curriculum. Multiple features characterize representations in textbooks, such as instructional guidance, function, and spatial contiguity (Slough et al., 2010; Gkitzia et al., 2011). It is important to understand these various features, and how they aid in understanding of associated content, since these characteristics should be significant criteria in choosing and assigning textbooks as resources for students. While studies have been conducted looking at representations in general chemistry textbooks at the high school level (e.g.Gkitzia et al., 2011), this study examines representations in textbooks at the collegiate level. We use the cognitive load theory to draw implications of the features of representations in the five textbooks.
Representations are a prominent feature of modern day science textbooks. As Lee (2010) notes, “representations have become one of the most pervasive and visible elements of the modern-day science textbook” (p. 1099). When properly designed, representations can aid understanding of scientific ideas. However, their prevalence in textbooks has been a source of criticism, with some believing that they are in excess (Woodward, 1992). Representations can also cause confusion to students; to a point of being counterproductive to the very learning they are supposed to enhance (Linn and Hsi, 2000; Stern and Roseman, 2004). For this very reason, it is important that representations used in textbooks be reviewed to ensure they are relevant and will contribute to student learning.
Representations in textbooks serve a number of functions. Representations can be decorative, ‘representational’, organizational or interpretational (Slough et al., 2010). A decorative representation is not explicitly conceptually related to the associated text, and therefore does not support the text; an example could be a colorful molecule on the side of the page with no explanation as to how that molecule is relevant to the text or concept. A representational illustration (representation) complements text in communicating a concept – makes the information in the text concrete (Slough et al., 2010). For example, a three dimensional molecule where bond angles were highlighted could help a student visualize molecular shapes. Organizational representations summarize information into a form such as a table, map, or a graph. An interpretational representation goes beyond an organizational representation (Slough et al., 2010) by including additional information that may not be in associated text. Interpretational representations may include contextual details or useful information that would otherwise hinder the “flow” of the text, such a table of thermodynamic constants or experimental data.
Three ‘types’ of cognitive load are associated with instructional material in textbooks: intrinsic cognitive load, germane cognitive load and extraneous cognitive load (Sweller, 1994; Cook, 2006). Intrinsic cognitive load is associated with the nature of the subject matter. For example, chemistry is multirepresentational, requiring learners to translate between and within representations that portray conceptual elements at the macroscopic and submicroscopic levels, sometimes simultaneously. This fact makes chemistry challenging to students (Johnstone, 2000). Representations and text require simultaneous processing and integration in order to facilitate understanding. If the number of interacting elements (elements that require integration to be understood) is high, the intrinsic cognitive load likely to be associated with them will be high, increasing the possibility of exceeding working memory capacity (Cook, 2006). For any given content area, intrinsic cognitive load is expected/constant since it is a function of the subject matter of that discipline (Sweller, 1994).
Germane cognitive load is experienced during the process of schema formation and automation (Cook, 2006). Schemas are ‘units of knowledge’ stored in long-term memory for later retrieval (Sweller, 1994). Facilitated by instructional design, germane cognitive load is beneficial to learning (Cierniak et al., 2009). According to Kirschner (2002), extraneous cognitive load is associated with poorly designed instructional materials, which require more cognitive resources to process. Resources devoted to process poorly designed instructional materials take away from meaningful learning (Kalyuga et al., 1999). Thus, extraneous cognitive load hinders learning (Cierniak et al., 2009). According to Cook (2006), both germane and extraneous cognitive load can be mitigated through instructional design. Ideally, the design of instructional materials should involve reducing extraneous cognitive load while increasing germane cognitive load (Cierniak et al. 2009). Of particular importance to this study is extraneous cognitive load, which results from poor instructional design (Kirschner, 2002).
The utility of multiple representations depends on the extent to which learners understand information contained in a given representation (Van der Meij, 2007). However, learners also have to translate between and within the different representations, a factor believed to enhance conceptual understanding and formation of a coherent mental model (Seufert, 2003; Schnotz, 2008; Berthold and Renkl, 2009). An important factor in integrating information in or from representations depends on the number of representations, and ultimately, the amount of information students need to integrate. In a recent study, Corradi et al. (2014) found that students with low prior knowledge struggled when presented with more than two representations alongside text that they were to integrate. If the number of representations that require simultaneous integration increases beyond what can be processed in working memory, learning will be hindered (Kalyuga et al., 2003; Cook, 2006). It is worth noting that this is more the case with low prior knowledge learners. For experts, the integration does not impose as high a cognitive load. To reduce this kind of cognitive load, it may be necessary to reduce the number of representations required to communicate a concept. This obviously raises the question of whether all representations used in textbooks (alongside text) are necessary. Corradi et al. (2012) found that when presented with multiple representations, students tended to focus on only one representation. We contend then, based on their results, that it may not be useful to present more/many representations to students which they may not pay attention to.
Despite the possibility of inducing a high cognitive load through the integration of multiple representations, representations that together communicate a given concept should be integrated instead of being presented separately. Multiple representations used in general chemistry textbooks require integration either between representations or with text in order to understand associated concepts. For this reason, the material is likely to impose intrinsic load (Sweller and Chandler, 1994). However, the representations and text cannot stand alone and need to be ‘used’ together. The process of integrating representations with text has the potential to impose high extraneous cognitive load if the integration is hindered by instructional design, especially for learners with low prior knowledge and limited working memory (Cook, 2006). This problem is exacerbated when a representation is distal or proximal to the referencing text. A learner's attention is split in the process of going back-and forth between text and representations, which may be on different pages. As Wu and Shah (2004) note, one way to reduce such cognitive load is to present text and accompanying representations close together, to help learners easily form associations between them. When designing instructional material, such as textbooks, efforts should be made to avoid ‘splitting learner's attention’, which could lead to extraneous cognitive load (Cook, 2006).
Captions and labels offer instructional guidance to support learning with representations by pointing out important features or information about a representation, thereby helping learners to focus on more than just surface features (Bodemer and Faust, 2006; Seufert and Brunken, 2006; Van der Meij, 2007; Gkitzia et al., 2011). Extended captions help students learn with graphics (Gkitzia et al., 2011). Research has shown that directives such as captions are more effective when they require active processing from a reader (the learner). With respect to captions, this means that they ‘engage’ learners by asking them to pay attention to specific aspects of a representation (Peeck, 1993). Also important are labels that accompany representations. Labels point to the different elements of a representation, thereby facilitating learning from the representations (Mayer and Gallini, 1990). While there is research indicating that students may not necessarily use captions as aids (Schnotz, 2008), we believe that the intention of having them accompany representations is so that they can help learners better make sense of those representations.
Indexing is another form of instructional guidance. Through indexing, text explicitly references a representation, using conventions such as “see figure x.x” (Slough et al., 2010). Readers are, as a result, able to relate representations to associated text. This is what directs a reader to text and representations that require integration. It is also common in general chemistry for mathematical equations to be indexed, usually by assigning the given equation a number and chapter. In most cases, this numbering system helps link the equation with associated text. In other cases, when authors use an equation in more than one page or chapter, this indexing helps locate the equation, or make associations between related concepts explicit.
A random sample of textbook pages was obtained for each textbook through the use of a random number generator (http://www.random.org). A sufficient total number of pages were selected and analyzed from each text to provide a sample with a 95% confidence of being representative. (Cohen et al., 2011). Since each book was of a different length, this method allowed us to select an appropriate sample size for each book (i.e. larger books had larger sample sizes). The number of pages analyzed per book ranged from 216 to 235 pages. If one of the pages selected by the random number generator was a duplicate page, a new page that fell between the previous and following selected pages was randomly chosen. Because the focus of the study was not how representations were used in questions, pages that contained only review/end of chapter questions were not analyzed. Nearly all chapters in each book had at least one page that was analyzed, so representations were studied in a variety of chemistry topics in all of the texts. Due to the consistent nature in the layout of each textbook, there is a high likelihood that our randomly selected pages do constitute a representational sample that gives a comprehensive picture of representation characteristics for each text.
During the coding process, each page was analyzed separately; the number of representations on that page that fit in a given category were tallied and recorded. To establish inter-rater agreement, we coded common pages randomly picked from each of the five textbooks and compared our results. Our individual codes were tracked in Excel. The number of coding boxes which exhibited agreement were counted and converted into a percentage in order to establish inter-rater agreement which was 91% across the 5 textbooks. Differences were resolved through discussion. We then divided the remaining sampled pages into groups of 20 pages each. Each coder analyzed alternating groups of 20 pages (i.e. coder 1 analyzed the first set of 20 pages, the third set, fifth set, etc.). In this way, no textbook was coded solely by one researcher, and any differences in coding bias between the two researchers were distributed throughout the entire textbook. These procedures were repeated for every textbook used. With each textbook, the two researchers made sure that there was agreement of all codes in all categories through discussion. In the following section, categories used in the study are described, and illustrations for some of the categories where we felt it was necessary, are provided.
Distal: placement requires you to turn a page to see the index/most relevant content text.
Facing: representation and index/most relevant content text are on facing pages.
Proximal: representation and the index/most relevant content text are on the same page, but separated by one half page or more of text.
Direct: the index/most relevant content text and representation are directly adjacent to each-other or are closer than half a page.
Representational: the representation is presenting content that is already in the text in a new way – adds concreteness. For example, an in-line symbolic representation adds concreteness to the process that is being described in words by presenting it in another format.
Decorative: the representation does not serve to meaningfully increase student understanding of the conceptual topic at hand. Deleting the representation would not negatively impact conceptual understanding.
Organizational: the representation adds coherence. Such a representation summarizes or organizes the content that was presented in the text. For example, such representations summarize concepts, link concepts together, or provide chapter layouts.
Interpretational: adds information that was not presented in the text thereby helping support more difficult or unfamiliar concepts. Usually adds an element of organization as well in that it is giving more context to the content being presented. Tables presenting data or constants for substances are considered to be interpretational.
Fig. 1 below shows a page taken from Brown et al. (2015) illustrating some of the categories described above:
Category | Code/representation |
---|---|
Number of representations | 6 (Numbered 1–6). |
Function | Representational (eqn (3)–(6)) |
Interpretational (Table 15.1 and Figure 15.5) | |
Physical integration | Representation 1 (Table 15.1 is ‘facing’). |
All others are directly integrated | |
Labels | Table 15.1 and Figure 15.5 (both require labels) |
Indexing | Table 15.1 is indexed on a different page |
Figure 15.5 is indexed on the same page | |
Captions | Figure 15.5 has a caption (Figure 15.5 is the only one needing a caption on the page. The label is sufficient for table 15.1) |
Integration groups | a. Representation 1 and associated text |
b. Representation 2 and associated text | |
c. Representation 3 and 4 and associated text | |
d. Representation 5 and 6 and associated text | |
Interacting groups | Representation 1 and text, with representation 2 and text make two interacting groups of representations as the two need to be integrated. |
On the page, no cross-referencing is needed for the other groups-therefore the groups do not interact. |
In Fig. 2 above representation/eqn (1) and text is one group, text and representations/eqn (2)–(5) is another group, representation/eqn (2) is integrated with both representation/eqn (3) and (4) (making two groups), representations/eqn (2)–(4) interact with eqn (5), and eqn (5) interacts with eqn (6). Representation 7 interacts with all of the six previous representations, and text, making an interacting group of 8 in total.
Book | Average total number of representations per page |
---|---|
Chang and Goldsby | 3.63 |
Gilbert et al. | 3.80 |
Brown et al. | 3.79 |
Tro | 4.21 |
Silberberg and Amateis | 4.31 |
All 5 textbooks had on average, about four representations per page. This means that in addition to text, there were four other representations that were associated with given text on a given page. While not always true, there is a very high likelihood that the representations are related to the same concept. As such, a student will need to integrate on average four representations with text while reading a page of each of the textbooks. While representations on a page pertain to one topic, it is possible that a page has two sub-topics. As an example, in Fig. 1 above, there are two related sub-topics on the page. In a recent study, Corradi et al. (2014) found that students with low prior knowledge struggled more when they were presented with two representations alongside text than when presented with text plus one representation. Students with low prior knowledge are therefore likely to struggle reading the textbooks we analyzed, given that the average total number of representations per page, alongside text is more than two. The high average number of representations per page could imply high intrinsic cognitive load (Sweller, 1994; Cook, 2006).
Book/function (%) | Representational | Decorative | Interpretational | Organizational |
---|---|---|---|---|
Chang and Goldsby | 79 (592/753) | 14 (108/753) | 5 (35/753) | 2 (18/753) |
Gilbert et al. | 86 (737/857) | 9 (80/857) | 2 (13/857) | 3 (27/857) |
Brown et al. | 90 (772/857) | 5 (45/857) | 2 (20/857) | 2 (20/857) |
Tro | 89 (842/948) | 7 (68/948) | 1 (11/948) | 3 (27/948) |
Silberberg and Amateis | 85 (802/947) | 8 (76/947) | 4 (36/947) | 3 (33/947) |
Of the total number of representations analyzed, a majority served a ‘representational’ function (i.e. the representation was related to information that was discussed or described in the text), and some served organizational and interpretational functions. All of these help students understand associated concepts with explicitly provided links to the content and could be considered ‘instructionally useful’ representations. However, an interesting finding in this analysis is that across the five textbooks decorative representations are the second most prevalent class of representations. These representations were classified as ‘decorative’ since they did not have a conceptual connection to content on a given page. Decorative representations are extraneous material (Mayer, 2001, 2003), which add extraneous cognitive load, and are therefore likely to take away from cognitive resources devoted to learning (Cook, 2006). We should note here that any speculation on the role of representations we considered decorative is beyond the scope of this work. We are not saying that decorative representations are necessarily bad: we hope to highlight the implications of those representations on cognitive load and how they are therefore likely to impact learning from textbooks.
Book/physical integration % (occurrences) | Distal | Facing | Proximal | Direct |
---|---|---|---|---|
Chang and Goldsby | 5 (35/747) | 3 (31/747) | 3 (19/747) | 89 (662/747) |
Gilbert et al. | 7 (56/850) | 9 (83/850) | 4 (34/850) | 80 (677/850) |
Brown et al. | 7 (60/856) | 8 (67/856) | 5 (44/856) | 80 (685/856) |
Tro | 2 (22/934) | 8 (70/934) | 5 (44/934) | 85 (798/934) |
Silberberg and Amateis | 3 (28/938) | 9 (88/938) | 3 (31/938) | 84 (791/938) |
Physical integration refers to the proximity of a representation to its related text and/or referencing index. Of the representations analyzed, a majority, at least 80% of representations in all textbooks were within one half a page of their associated text, i.e. directly integrated. However, the fact that there are representations that are distal (requires a turn of page between text and representation), or facing (text and representation are on facing pages), or proximal (text and representation are on the same page, but further than a half a page apart) is likely to pose challenges to students as they go between text and representations, especially as is the case with representations that are distal to text. As McTigue and Slough (2010) note, “students should not be expected to flip pages to find referent graphics, and most readers will simply not put forth such effort” (p. 223). This will of course mean that the desired conceptual integration between text and representations will not occur. We believe that a number of factors, such as the size of a given representation determine placement of representations. For example, a large table may not fit on the same page as associated text, necessitating a facing or distal placement. While the placement is justified, flipping a page as one goes between text and representation has implications for extraneous cognitive load. A closer examination of representations that were either distal or facing to associated text across the five textbooks indicated that only one-third were large tables. Representations which are spatially closer to their associated text present less (extraneous) cognitive load than if they were more spatially separated (Plass et al., 2009).
Book/indexing % (occurrences) | Same page | Different page | Unindexed |
---|---|---|---|
Chang and Goldsby | 44 (129/296) | 17 (51/296) | 39 (116/296) |
Gilbert et al. | 68 (223/328) | 27 (89/328) | 5 (16/328) |
Brown et al. | 67 (185/278) | 29 (80/278) | 5 (13/278) |
Tro | 66 (148/225) | 8 (19/225) | 26 (58/225) |
Silberberg and Amateis | 77 (252/329) | 19 (61/329) | 5 (16/329) |
The percentage of representations indexed (using conventions such as Figure x.x or Table x) varied among different books, as shown in Table 5 below. All five textbooks had most representations indexed within the same page. This is a positive feature since indexing is a form of instructional guidance which directs students to view a representation associated with text. In each textbook however, there is a significant percentage of representations either indexed on a different page, or not indexed at all. Ideally, representations should be indexed, and be on the same page as the associated text. When indexed representations are on a different page, a student would have to flip to the particular page, and then back to text, a process that will likely lead to loss of concentration. Of concern is the high proportion of representations that are either indexed on a different page or not indexed at all in all five the textbooks (25–56%), as this assumes that students will figure out text and representation associations, which may not always be possible. This is an indication of poor design of instructional materials. Indexing can decrease cognitive load by cueing students when to look at a representation (Plass et al., 2009) and helping students to conceptually integrate material (Slough et al., 2010). Thus, unindexed representations add to extraneous cognitive load.
Book/caption % (occurrences) | Exists | Does not exist |
---|---|---|
Chang and Goldsby | 89 (263/296) | 11 (33/296) |
Gilbert et al. | 96 (313/326) | 4 (13/326) |
Brown et al. | 97 (269/278) | 3 (9/278) |
Tro | 92 (206/225) | 8 (19/225) |
Silberberg and Amateis | 93 (306/329) | 7 (23/329) |
As can be seen in Table 6, across the five textbooks, most of the analyzed representations had captions, ranging in proportion from 89% to 96%, which is an encouraging trend. On the other hand the absence of captions (between 4% and 11%) is likely to leave a student struggling to make sense of a representation. Captions provide instructional guidance (Pozzer and Roth, 2003; Gkitzia et al., 2011) which often helps to decrease extraneous cognitive load (Cook, 2006). Specifically, extended captions describe a given representation, thereby helping students understand information in that representation. An absence of a caption in a representation leads to extraneous cognitive load, as learners would have to figure out on their own what a representation shows, and they may not always succeed in this.
Book/labels % (occurrences) | With labels | No labels |
---|---|---|
Chang and Goldsby | 68 (201/296) | 32 (95/296) |
Gilbert et al. | 83 (272/326) | 17 (54/326) |
Brown et al. | 90 (249/278) | 10 (29/278) |
Tro | 84 (189/225) | 16 (36/225) |
Silberberg and Amateis | 93 (305/329) | 7 (24/329) |
Labels, as a form of instructional guidance, play an important role in defining a representation, informing readers of what is in a representation. For example, a data table without a label leaves a reader wondering what information the table is portraying. A high percentage of representations analyzed across the five textbooks contained labels. However, as can be seen in Table 7, the proportions of representations without labels ranges from 7–32%, painting a less than ideal picture, especially in the case of the Chang and Goldsby textbook. Not every representation may require a label, but ideally, nothing should be left to the second-guessing of a reader as they process a representation. Across the five textbooks, lack of labels was most common in pictures, symbolic representations, and space filling models, where components were not labelled. Less common were missing labels in tables and graphs. For graphs, the most common missing label was the title, although to a small extent there were graphs missing labels of axes. For tables, the title was the most common missing label. As part of instructional guidance, necessary labels, such as titles should be included in representations. This level of guidance would certainly help decrease extraneous cognitive load (Cook, 2006).
An important observation we should make is that the same representations were coded for the caption and labels categories – a representation that had a caption likely also had a label. To a less extent, in each textbook, there were representations that had captions only or labels only. Table 8 below shows the relative percent occurrence of representations which had a caption and label(s), a caption only and a label only in each of the five textbooks.
Book/caption and label % (occurrences) | Caption and label | Caption only | Label only |
---|---|---|---|
Chang and Goldsby | 57 (168/296) | 32 (95/296) | 11 (33/296) |
Gilbert et al. | 79 (259/326) | 17 (54/326) | 4 (13/326) |
Brown et al. | 86 (240/278) | 11 (29/278) | 3 (9/278) |
Tro | 76 (170/225) | 16 (36/225) | 8 (19/225) |
Silberberg and Amateis | 86 (282/329) | 7 (24/329) | 7 (23/329) |
Book/group size occurrences % (occurrences) | 2 | 3 | 4 | ≥5 |
---|---|---|---|---|
Chang and Goldsby | 81 (390/481) | 14 (67/481) | 3 (16/481) | 2 (8/481) |
Gilbert et al. | 65 (302/466) | 19 (90/466) | 10 (45/466) | 6 (29/466) |
Brown et al. | 67 (339/507) | 17 (86/507) | 10 (53/507) | 6 (29/507) |
Tro | 68 (363/534) | 18 (97/534) | 8 (42/534) | 6 (32/534) |
Silberberg and Amateis | 76 (442/580) | 13 (73/580) | 7 (39/580) | 4 (26/580) |
A majority of the representations required the reader to conceptually integrate one or two representations with the text and/or another representation to achieve understanding. Across the five textbooks, there were instances where students were required to conceptually integrate more than four representations with text. In a study by Corradi et al. (2014), students struggled when they were required to integrate text with more than one representation simultaneously. Working memory can be overburdened if many elements of novel information require simultaneous processing, as is the case with many representations requiring integration with text (Sombatteera and Kalyuga, 2012). If material is new to learners (especially learners with low or no prior knowledge), the more representations one has to integrate with text, the more overload they are likely to experience due to intrinsic cognitive load.
Text/groups per page % (occurrences) | 1 | 2 | 3 | 4 | 5 | ≥6 |
---|---|---|---|---|---|---|
Chang and Goldsby | 22 (43/193) | 35 (68/193) | 25 (48/193) | 10 (19/193) | 6 (11/193) | 2 (4/193) |
Gilbert et al. | 23 (46/203) | 44 (90/203) | 20 (40/203) | 8 (17/203) | 4 (8/203) | 1 (2/203) |
Brown et al. | 24 (53/219) | 36 (79/219) | 27 (59/219) | 10 (22/219) | 2 (5/219) | 0 (1/219) |
Tro | 20 (42/205) | 33 (67/205) | 26 (53/205) | 14 (29/205) | 3 (7/205) | 3 (7/205) |
Silberberg and Amateis | 20 (40/197) | 26 (52/197) | 20 (40/197) | 18 (36/197) | 6 (12/197) | 9 (17/197) |
Table 10 below shows that in most cases across the five textbooks between one and three integrated groups of representations are present on a given page. There is, however, a (albeit small) percentage of cases where there are up six or more groups of integrated representations on a given page. A close examination of cases where such high numbers of interacting groups were found showed that most were related to the same topic content. We feel that such a high number of groups makes for a ‘noisy’ page, which in itself could overwhelm a student. If the representations are all necessary for understanding associated concepts, four, five and six groups of representations would certainly make for high intrinsic cognitive load. It would be especially important in these cases where necessary to use aspects of instructional guidance (captions, labels, indexing, etc.) to assist students.
In the five textbooks used for this study, there were an average of four representations per page. This fact both confirms the multi-representational nature of chemistry, and the role that representations play in enhancing understanding of chemistry content by playing a supporting and complementary role to text in communicating content (Pozzer and Roth, 2003; Taber, 2013). Indeed, our analysis of the function of representations shows that most representations support conceptual understanding, since most fall into one of three categories (‘representational’, organizational, and interpretational). While these findings paint a positive picture of the use of representations in the textbooks, research has also shown that when students, especially those with low prior knowledge are presented with more than two representations that require integration with text, they get overwhelmed (Corradi et al., 2014). In the context of this study, such students are likely to experience high intrinsic cognitive load.
In this study, we found that textbook authors employed various design features and instructional guidance that we felt will help students as they read the textbooks, especially in the context of decreasing cognitive load associated with using representations in textbooks. Specifically, the use of labels, extended captions, indexing of representations within running text (on the same page), and physically integrating representations with text (direct or proximal) are features that will not only help enhance the integration of text and representations, but also decrease extraneous cognitive load associated with instructional design (Cook, 2006).
It is worth noting however that in each of the categories related to instructional design, there are features of representations in the five textbooks that indicate poor instructional design, which is likely to lead to extraneous cognitive load. Specifically, representations without labels, representations that were either not indexed or indexed on a different page, decorative representations, representations that did not have an extended caption, and representations that were facing or distal to text are all elements of poor instructional design, which is likely to add to extraneous cognitive load (Sweller, 1994; Cook, 2006).
In using representations in chemistry textbooks, the expectation is that they be integrated with text to bring about conceptual understanding. Our results show that in most cases, across the five textbooks, students need to simultaneously integrate between one and two representations with text to attain conceptual understanding. In the study by Corradi et al. (2014), students with low prior knowledge were successful at integrating one representation with text, but struggled when asked to integrate two representations with text. In each of the textbooks, though to a small extent, students need to integrate more than three representations with text. Even though students may not necessarily look at all representations, we believe the representations are necessary for understanding of target concepts. Especially for students with low or no prior knowledge, a high number of representations requiring conceptual integration with text will be challenging (Sombatteera and Kalyuga, 2012) and likely impose high intrinsic cognitive load.
Alongside integrating representations with text, students are sometimes required to integrate ‘groups’ of text and representations together for conceptual understanding. An analysis of cases where this was evident in the textbooks showed that this involved related content, where an idea was being developed through a combination of text and equations. As an example, in Fig. 2 above, taken from a chapter on thermochemistry, is an example on using enthalpies of formation to calculate enthalpies of reaction. This certainly is an example of a context where students will likely experience intrinsic cognitive load due to the nature of the content. Given this reality, it is encouraging that on that particular page, there is no extraneous material, and that the associated representations are directly integrated with text.
In conclusion, an analysis of the five textbooks shows that representations are used ‘extensively’ in each textbook given the average number of representations in each textbook. Our findings present a ‘mixed message’ with respect to features of representations that enhance or are likely to hinder understanding and learning when using textbooks as seen through the lens of the cognitive load theory. A general encouraging trend across the five textbooks is notable: a number of design features as well as instructional guidance are used across the five textbooks which we believe help decrease cognitive load experienced while using textbooks. However, in each of these categories, there are features of representations that indicate poor instructional design, which will add extraneous cognitive load and likely hinder learning (Cook, 2006). Chemistry is a multirepresentational discipline, which is also abstract in nature (Johnstone, 2000; Talanquer, 2011; Taber, 2013). By its very nature, the subject possesses intrinsic cognitive load (Mayer, 2001; Cook, 2006). The extent to which one experiences the intrinsic cognitive load depends on factors such as prior knowledge and instructional design (Cook, 2006; Slough et al., 2010). While intrinsic cognitive load will therefore be ‘expected’ in chemistry, extraneous cognitive load ‘amplifies’ its effect (Sweller, 1994; Cook, 2006). Since the extraneous cognitive load we anticipate from the analyses above in each textbook is mostly related to instructional design, there is a chance to reduce the extraneous cognitive load and consequently its impact on learning from the textbooks.
For textbook authors and publishers, our findings have implications for how representations, as used in textbooks, may or may not support learning. The textbooks we analyzed in this study are generally good models based on what we sought to study. In each textbook however, there are a number of elements of representations that could be improved. While one can appreciate the fact that a number of considerations go into for example placement of a figure in a textbook, one consideration has to be how easy a representation will be to use, based on how close it is to the accompanying text. For example, as Sweller (1994) notes, extraneous cognitive load, which can be mitigated through instructional design, should be an important consideration for designing instructional material. Any elements that could contribute to extraneous cognitive load should be avoided.
Our research and findings have implications for teacher preparation. One criticism that has specifically been labelled against teacher education programs is that they do not prepare science teachers in the area of curriculum selection, specifically selection of textbooks (Seufert, 2003). As noted by Cook (2006), representations, especially those considered decorative, have unfortunately been used for purposes of marketing. As science teachers choose curriculum materials, such as textbooks, they need criteria to go by. Our study, as well as others, such as Slough et al. (2010) provides a model of such criteria. For science teacher educators, we recommend that we engage in such an exercise to help pre-service teachers learn how to apply such criteria and make decisions on suitability of textbooks.
A second limitation stems from the fact that we sampled pages from each of the five textbooks and did not examine every page in the texts. We know that the number of representations for example vary depending on the chapter – so that some chapters will by their nature contain more representations than others. However, as noted in the methodology section, we believe the number of pages sampled from each textbook is high enough to make it representative.
There are a few potential projects we would like to pursue. First, since chemistry students are expected to be diverse, based on aspects such as prior knowledge, it will be useful to research how students on the prior knowledge continuum interact with text and representations (Cook, 2006). A recent study by Corradi et al. (2014) involved students with low prior knowledge. We are interested in using a population of students with high levels of prior knowledge as a comparison to the Corradi et al. (2014) study.
Another important study we wish to explore involves eye tracking to see how students translate between text and representations. We are interested in tracking a learner's ‘path’ as they read a page and integrate text and representations. In cases where multiple representations need to be integrated with text to attain conceptual understanding, we would like to determine whether learners integrate all representations that are necessary for conceptual understanding. Such an eye tracking study could also yield implications for the design layout of textbooks.
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