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IntroductionChemical education rese
Introduction
Chemical education researchers interested in evaluating and improving students’ abilities to visualize chemical phenomena at the particulate level have demonstrated that the use of computer animations depicting chemical processes at the particulate level can improve chemistry students’ visualization skills (Williamson and Abraham, 1995; Russell et al., 1997; Sanger and Greenbowe, 2000; Sanger et al., 2000, 2001, 2007; Sanger and Badger, 2001; Ardac and Akaygun, 2004; Kelly et al., 2004; Vela´zquez-Marcano et al., 2004; Tasker and Dalton, 2006; Kelly and Jones, 2007, 2008; Gregorius et al., 2010a, 2010b; Rosenthal and Sanger, 2012, 2013a, 2013b;Williamson et al., 2012).
Most of this research used these particulate-level computer
animations as part of instructional interventions designed to improve students’ conceptual understanding of chemical phenomena. This study is one of a growing number that have started to use these animations as part of the assessment process (Sanger et al., 2007; Naah and Sanger, 2012, 2013; Rosenthal and Sanger, 2012, 2013a, 2013b). Rosenthal and Sanger (2013a) compared the particulate explanations of an oxidation–reduction reaction involving copper metal and an aqueous silver nitrate solution from two groups of students who had viewed a chemical demonstration of this reaction and one of two different particulate-level computer animations of this reaction. The two animations depicted the same chemical reaction, but differed in the levels of complexity of the visual images used in these animations. The animation created by Michael J. Sanger (referred to as the
‘more simplified animation’) used a static camera angle, did not depict water molecules in solution, and depicted objects moving and colliding in a single plane. The animation created as part of the VisChem project (Tasker and Dalton, 2006), and referred to as the ‘more complex animation’, used a changing camera angle, solution, and allowed objects to move in front of or behind each other. This study showed that students viewing the more simplified animation provided better explanations for eight different concepts related to the oxidation–reduction reaction compared to the students viewing the more complex animation.
Students viewing the more simplified animation also provided more accurate balanced chemical equations for this reaction compared to the students viewing the more complex animation. Quotes from students in both groups suggested that those viewing the more complex animation underperformed compared to those viewing the more simplified animation because themore complex animation depicted extraneous information and either did not depict relevant information or depicted relevant information that was difficult for students to see due to the detrimental effects of the extraneous information. In a follow-up study, Rosenthal and Sanger (2013b) compared how the order of viewing the two different animations of the copper–silver nitrate oxidation–reduction reaction affected the students’ particulate-level explanations of this reaction. They found that students who viewed the more complex
animation followed by the more simplified animation provided better explanations for seven concepts and provided more correct balanced chemical equations than those students who viewed the animations in the reverse order. Students who favoured showing the more complex animation followed by the more simplified animation believed that the more complex animation will get students’ attention (by entertaining or confusing them), and then the more simplified animation will more clearly explain what is happening in the reaction, leading to improved learning. However, interpretation of the results from this study are complicated by the fact that many of the students’ explanations were directly tied to the version of the animation they were viewing, and so the differences in their explanations may be an artefact of the last animation viewed and not necessarily the order in which the two animations were viewed.
One of the conclusions from this last study (Rosenthal and Sanger, 2013b) was that viewing the more simplified animation served as an instructional cue (Mayer and Gallini, 1990; Patrick et al., 2005; Mayer and Wittrock, 2009; Cook et al., 2011; Lin
and Atkinson, 2011) that assisted students in interpreting the more complex animation. However, this assertion was not specifically tested in that study. The goal of the present study is to determine how viewing one of the animations affects the
participants’ subsequent explanations of the other animation. Theoretical framework
When describing chemical phenomena, chemists often use three related but distinct representational levels—the macroscopic, particulate, and symbolic levels (Johnstone, 1993; Gilbert and Treagust, 2009; Johnstone, 2010; Talanquer,
2011). The macroscopic representation involves qualitative observations of chemical phenomena made using the five senses (colour changes, odours, heat changes, etc.), the particulate representation involves the behaviour of atoms, molecules, and
ions involved in the chemical phenomena, and the symbolic representation involves the use symbols (numbers, mathematical formulas, chemical symbols and formulas, balanced equations, etc.) to represent more abstract concepts.
The effectiveness of using computer animations of chemical processes at the particulate level is based on Mayer’s cognitive theory of multimedia learning (Mayer, 2001), which was adapted from Paivio’s dual-coding theory (Paivio, 1986) and Baddeley’s model of working memory (Baddeley, 1986). Mayer’s theory assumes that learners possess separate cognitive channels for processing visual (pictorial) and auditory (verbal) information, that learners have limited processing capabilities in each channel, and that learners engage in active learning by attending to relevant information, organizing this information into mental schema, and integrating this new knowledge with pre-existing knowledge.
Mayer’s theory of multimedia learning incorporates cognitive load theory (Baddeley, 1986; Sweller, 1994; Sweller and Chandler, 1994), which assumes that learners have limited working memory and an unlimited long-term memory. If the cognitive load of the instructional lesson exceeds the limits of the learner’s working memory, then learning will be hampered or diminished. There are two types of cognitive load that affect learning (Sweller, 1994; Sweller and Chandler, 1994). Intrinsic cognitive load is a property of the content to be learned; concepts that can be processed sequentially and independently of one another represent low intrinsic load, while concepts that must be processed simultaneously represent a higher intrinsic load. Extraneous cognitive load, on the other hand, is a function of how the instructional material is presented. Since the way a lesson is presented does not change the content to be learned, any extraneous cognitive load imposed by the way in which the lesson is presented uses up cognitive resources without improving learning (Lee et al., 2006).
Therefore, the goal of instructional design is to reduce extraneous cognitive load by manipulating verbal (text and narration) and pictorial information. For example, Mayer (2001) provides seven principles of multimedia design to minimize extraneous cognitive load based on the results of several educational research studies. Other researchers (Lee et al., 2006; Homer and Plass, 2010) have shown that adding iconic information to the symbolic visuals used in computer animations can improve student learning by minimizing extraneous cognitive load. Symbolic visuals use arbitrary representations to depict an object or concept, while iconic visuals use representations that are tied to the object or concept by surface-level relationships (e.g., when depicting an object being heated, using a slide bar with the word ‘Temperature’ above it represents symbolic visuals; showing the addition or removal of Bunsen burners below the object being heated or cooled represents iconic visuals). These researchers have shown that the positive effects of providing iconic information are largest when the students have low prior knowledge and when the concepts are highly complex (Lee et al., 2006; Kalyuga, 2007; Homer and Plass, 2010). Methodology
Subjects
The sample consisted of 55 volunteer students (19 males and 36 females) enrolled in the same section of a second-semester introductory chemistry course intended for chemistry, biology, and health science majors and taught by the same chemistry instructor. Each participant was interviewed for 40–70 min after receiving classroom instruction on oxidation–reduction reactions and electrochemistry. The participants were randomly assigned via coin toss to one of two groups—one group (N = 26) viewed the more simplified animation before viewing the more complex animation while the other group (N = 29) viewed the more complex animation before the more simplified animation.
Computer animations
The more simplified animation of the silver–copper reaction was created by the second author (Fig. 1a). This program was animated as two-dimensional such that when two objects approached each other, they were animated as colliding and
bouncing off one another. The total viewing time for this animation is about 30 s; this animation was shown to the participants without narration. The animation shows coppercoloured circles in an organized pattern (copper metal) placed against a blue background (water). In the blue background, several silver-coloured circles with a ‘+’ symbol (silver ions) and an equal number of blue/red atom clusters with a ‘’ symbol on it (nitrate ions) move freely. As the reaction occurs, two silver circles approach a copper circle, and a red ‘e’ (electron) is transferred from the copper circle to each of the two silver circles. When the ‘e’ are transferred, the copper ci
Chemical education researchers interested in evaluating and improving students’ abilities to visualize chemical phenomena at the particulate level have demonstrated that the use of computer animations depicting chemical processes at the particulate level can improve chemistry students’ visualization skills (Williamson and Abraham, 1995; Russell et al., 1997; Sanger and Greenbowe, 2000; Sanger et al., 2000, 2001, 2007; Sanger and Badger, 2001; Ardac and Akaygun, 2004; Kelly et al., 2004; Vela´zquez-Marcano et al., 2004; Tasker and Dalton, 2006; Kelly and Jones, 2007, 2008; Gregorius et al., 2010a, 2010b; Rosenthal and Sanger, 2012, 2013a, 2013b;Williamson et al., 2012).
Most of this research used these particulate-level computer
animations as part of instructional interventions designed to improve students’ conceptual understanding of chemical phenomena. This study is one of a growing number that have started to use these animations as part of the assessment process (Sanger et al., 2007; Naah and Sanger, 2012, 2013; Rosenthal and Sanger, 2012, 2013a, 2013b). Rosenthal and Sanger (2013a) compared the particulate explanations of an oxidation–reduction reaction involving copper metal and an aqueous silver nitrate solution from two groups of students who had viewed a chemical demonstration of this reaction and one of two different particulate-level computer animations of this reaction. The two animations depicted the same chemical reaction, but differed in the levels of complexity of the visual images used in these animations. The animation created by Michael J. Sanger (referred to as the
‘more simplified animation’) used a static camera angle, did not depict water molecules in solution, and depicted objects moving and colliding in a single plane. The animation created as part of the VisChem project (Tasker and Dalton, 2006), and referred to as the ‘more complex animation’, used a changing camera angle, solution, and allowed objects to move in front of or behind each other. This study showed that students viewing the more simplified animation provided better explanations for eight different concepts related to the oxidation–reduction reaction compared to the students viewing the more complex animation.
Students viewing the more simplified animation also provided more accurate balanced chemical equations for this reaction compared to the students viewing the more complex animation. Quotes from students in both groups suggested that those viewing the more complex animation underperformed compared to those viewing the more simplified animation because themore complex animation depicted extraneous information and either did not depict relevant information or depicted relevant information that was difficult for students to see due to the detrimental effects of the extraneous information. In a follow-up study, Rosenthal and Sanger (2013b) compared how the order of viewing the two different animations of the copper–silver nitrate oxidation–reduction reaction affected the students’ particulate-level explanations of this reaction. They found that students who viewed the more complex
animation followed by the more simplified animation provided better explanations for seven concepts and provided more correct balanced chemical equations than those students who viewed the animations in the reverse order. Students who favoured showing the more complex animation followed by the more simplified animation believed that the more complex animation will get students’ attention (by entertaining or confusing them), and then the more simplified animation will more clearly explain what is happening in the reaction, leading to improved learning. However, interpretation of the results from this study are complicated by the fact that many of the students’ explanations were directly tied to the version of the animation they were viewing, and so the differences in their explanations may be an artefact of the last animation viewed and not necessarily the order in which the two animations were viewed.
One of the conclusions from this last study (Rosenthal and Sanger, 2013b) was that viewing the more simplified animation served as an instructional cue (Mayer and Gallini, 1990; Patrick et al., 2005; Mayer and Wittrock, 2009; Cook et al., 2011; Lin
and Atkinson, 2011) that assisted students in interpreting the more complex animation. However, this assertion was not specifically tested in that study. The goal of the present study is to determine how viewing one of the animations affects the
participants’ subsequent explanations of the other animation. Theoretical framework
When describing chemical phenomena, chemists often use three related but distinct representational levels—the macroscopic, particulate, and symbolic levels (Johnstone, 1993; Gilbert and Treagust, 2009; Johnstone, 2010; Talanquer,
2011). The macroscopic representation involves qualitative observations of chemical phenomena made using the five senses (colour changes, odours, heat changes, etc.), the particulate representation involves the behaviour of atoms, molecules, and
ions involved in the chemical phenomena, and the symbolic representation involves the use symbols (numbers, mathematical formulas, chemical symbols and formulas, balanced equations, etc.) to represent more abstract concepts.
The effectiveness of using computer animations of chemical processes at the particulate level is based on Mayer’s cognitive theory of multimedia learning (Mayer, 2001), which was adapted from Paivio’s dual-coding theory (Paivio, 1986) and Baddeley’s model of working memory (Baddeley, 1986). Mayer’s theory assumes that learners possess separate cognitive channels for processing visual (pictorial) and auditory (verbal) information, that learners have limited processing capabilities in each channel, and that learners engage in active learning by attending to relevant information, organizing this information into mental schema, and integrating this new knowledge with pre-existing knowledge.
Mayer’s theory of multimedia learning incorporates cognitive load theory (Baddeley, 1986; Sweller, 1994; Sweller and Chandler, 1994), which assumes that learners have limited working memory and an unlimited long-term memory. If the cognitive load of the instructional lesson exceeds the limits of the learner’s working memory, then learning will be hampered or diminished. There are two types of cognitive load that affect learning (Sweller, 1994; Sweller and Chandler, 1994). Intrinsic cognitive load is a property of the content to be learned; concepts that can be processed sequentially and independently of one another represent low intrinsic load, while concepts that must be processed simultaneously represent a higher intrinsic load. Extraneous cognitive load, on the other hand, is a function of how the instructional material is presented. Since the way a lesson is presented does not change the content to be learned, any extraneous cognitive load imposed by the way in which the lesson is presented uses up cognitive resources without improving learning (Lee et al., 2006).
Therefore, the goal of instructional design is to reduce extraneous cognitive load by manipulating verbal (text and narration) and pictorial information. For example, Mayer (2001) provides seven principles of multimedia design to minimize extraneous cognitive load based on the results of several educational research studies. Other researchers (Lee et al., 2006; Homer and Plass, 2010) have shown that adding iconic information to the symbolic visuals used in computer animations can improve student learning by minimizing extraneous cognitive load. Symbolic visuals use arbitrary representations to depict an object or concept, while iconic visuals use representations that are tied to the object or concept by surface-level relationships (e.g., when depicting an object being heated, using a slide bar with the word ‘Temperature’ above it represents symbolic visuals; showing the addition or removal of Bunsen burners below the object being heated or cooled represents iconic visuals). These researchers have shown that the positive effects of providing iconic information are largest when the students have low prior knowledge and when the concepts are highly complex (Lee et al., 2006; Kalyuga, 2007; Homer and Plass, 2010). Methodology
Subjects
The sample consisted of 55 volunteer students (19 males and 36 females) enrolled in the same section of a second-semester introductory chemistry course intended for chemistry, biology, and health science majors and taught by the same chemistry instructor. Each participant was interviewed for 40–70 min after receiving classroom instruction on oxidation–reduction reactions and electrochemistry. The participants were randomly assigned via coin toss to one of two groups—one group (N = 26) viewed the more simplified animation before viewing the more complex animation while the other group (N = 29) viewed the more complex animation before the more simplified animation.
Computer animations
The more simplified animation of the silver–copper reaction was created by the second author (Fig. 1a). This program was animated as two-dimensional such that when two objects approached each other, they were animated as colliding and
bouncing off one another. The total viewing time for this animation is about 30 s; this animation was shown to the participants without narration. The animation shows coppercoloured circles in an organized pattern (copper metal) placed against a blue background (water). In the blue background, several silver-coloured circles with a ‘+’ symbol (silver ions) and an equal number of blue/red atom clusters with a ‘’ symbol on it (nitrate ions) move freely. As the reaction occurs, two silver circles approach a copper circle, and a red ‘e’ (electron) is transferred from the copper circle to each of the two silver circles. When the ‘e’ are transferred, the copper ci
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IntroductionChemical education researchers interested in evaluating and improving students’ abilities to visualize chemical phenomena at the particulate level have demonstrated that the use of computer animations depicting chemical processes at the particulate level can improve chemistry students’ visualization skills (Williamson and Abraham, 1995; Russell et al., 1997; Sanger and Greenbowe, 2000; Sanger et al., 2000, 2001, 2007; Sanger and Badger, 2001; Ardac and Akaygun, 2004; Kelly et al., 2004; Vela´zquez-Marcano et al., 2004; Tasker and Dalton, 2006; Kelly and Jones, 2007, 2008; Gregorius et al., 2010a, 2010b; Rosenthal and Sanger, 2012, 2013a, 2013b;Williamson et al., 2012).Most of this research used these particulate-level computeranimations as part of instructional interventions designed to improve students’ conceptual understanding of chemical phenomena. This study is one of a growing number that have started to use these animations as part of the assessment process (Sanger et al., 2007; Naah and Sanger, 2012, 2013; Rosenthal and Sanger, 2012, 2013a, 2013b). Rosenthal and Sanger (2013a) compared the particulate explanations of an oxidation–reduction reaction involving copper metal and an aqueous silver nitrate solution from two groups of students who had viewed a chemical demonstration of this reaction and one of two different particulate-level computer animations of this reaction. The two animations depicted the same chemical reaction, but differed in the levels of complexity of the visual images used in these animations. The animation created by Michael J. Sanger (referred to as the‘more simplified animation’) used a static camera angle, did not depict water molecules in solution, and depicted objects moving and colliding in a single plane. The animation created as part of the VisChem project (Tasker and Dalton, 2006), and referred to as the ‘more complex animation’, used a changing camera angle, solution, and allowed objects to move in front of or behind each other. This study showed that students viewing the more simplified animation provided better explanations for eight different concepts related to the oxidation–reduction reaction compared to the students viewing the more complex animation.Students viewing the more simplified animation also provided more accurate balanced chemical equations for this reaction compared to the students viewing the more complex animation. Quotes from students in both groups suggested that those viewing the more complex animation underperformed compared to those viewing the more simplified animation because themore complex animation depicted extraneous information and either did not depict relevant information or depicted relevant information that was difficult for students to see due to the detrimental effects of the extraneous information. In a follow-up study, Rosenthal and Sanger (2013b) compared how the order of viewing the two different animations of the copper–silver nitrate oxidation–reduction reaction affected the students’ particulate-level explanations of this reaction. They found that students who viewed the more complexanimation followed by the more simplified animation provided better explanations for seven concepts and provided more correct balanced chemical equations than those students who viewed the animations in the reverse order. Students who favoured showing the more complex animation followed by the more simplified animation believed that the more complex animation will get students’ attention (by entertaining or confusing them), and then the more simplified animation will more clearly explain what is happening in the reaction, leading to improved learning. However, interpretation of the results from this study are complicated by the fact that many of the students’ explanations were directly tied to the version of the animation they were viewing, and so the differences in their explanations may be an artefact of the last animation viewed and not necessarily the order in which the two animations were viewed.One of the conclusions from this last study (Rosenthal and Sanger, 2013b) was that viewing the more simplified animation served as an instructional cue (Mayer and Gallini, 1990; Patrick et al., 2005; Mayer and Wittrock, 2009; Cook et al., 2011; Linand Atkinson, 2011) that assisted students in interpreting the more complex animation. However, this assertion was not specifically tested in that study. The goal of the present study is to determine how viewing one of the animations affects theparticipants’ subsequent explanations of the other animation. Theoretical frameworkWhen describing chemical phenomena, chemists often use three related but distinct representational levels—the macroscopic, particulate, and symbolic levels (Johnstone, 1993; Gilbert and Treagust, 2009; Johnstone, 2010; Talanquer,2011). The macroscopic representation involves qualitative observations of chemical phenomena made using the five senses (colour changes, odours, heat changes, etc.), the particulate representation involves the behaviour of atoms, molecules, andions involved in the chemical phenomena, and the symbolic representation involves the use symbols (numbers, mathematical formulas, chemical symbols and formulas, balanced equations, etc.) to represent more abstract concepts.The effectiveness of using computer animations of chemical processes at the particulate level is based on Mayer’s cognitive theory of multimedia learning (Mayer, 2001), which was adapted from Paivio’s dual-coding theory (Paivio, 1986) and Baddeley’s model of working memory (Baddeley, 1986). Mayer’s theory assumes that learners possess separate cognitive channels for processing visual (pictorial) and auditory (verbal) information, that learners have limited processing capabilities in each channel, and that learners engage in active learning by attending to relevant information, organizing this information into mental schema, and integrating this new knowledge with pre-existing knowledge.Mayer’s theory of multimedia learning incorporates cognitive load theory (Baddeley, 1986; Sweller, 1994; Sweller and Chandler, 1994), which assumes that learners have limited working memory and an unlimited long-term memory. If the cognitive load of the instructional lesson exceeds the limits of the learner’s working memory, then learning will be hampered or diminished. There are two types of cognitive load that affect learning (Sweller, 1994; Sweller and Chandler, 1994). Intrinsic cognitive load is a property of the content to be learned; concepts that can be processed sequentially and independently of one another represent low intrinsic load, while concepts that must be processed simultaneously represent a higher intrinsic load. Extraneous cognitive load, on the other hand, is a function of how the instructional material is presented. Since the way a lesson is presented does not change the content to be learned, any extraneous cognitive load imposed by the way in which the lesson is presented uses up cognitive resources without improving learning (Lee et al., 2006).Therefore, the goal of instructional design is to reduce extraneous cognitive load by manipulating verbal (text and narration) and pictorial information. For example, Mayer (2001) provides seven principles of multimedia design to minimize extraneous cognitive load based on the results of several educational research studies. Other researchers (Lee et al., 2006; Homer and Plass, 2010) have shown that adding iconic information to the symbolic visuals used in computer animations can improve student learning by minimizing extraneous cognitive load. Symbolic visuals use arbitrary representations to depict an object or concept, while iconic visuals use representations that are tied to the object or concept by surface-level relationships (e.g., when depicting an object being heated, using a slide bar with the word ‘Temperature’ above it represents symbolic visuals; showing the addition or removal of Bunsen burners below the object being heated or cooled represents iconic visuals). These researchers have shown that the positive effects of providing iconic information are largest when the students have low prior knowledge and when the concepts are highly complex (Lee et al., 2006; Kalyuga, 2007; Homer and Plass, 2010). MethodologySubjectsThe sample consisted of 55 volunteer students (19 males and 36 females) enrolled in the same section of a second-semester introductory chemistry course intended for chemistry, biology, and health science majors and taught by the same chemistry instructor. Each participant was interviewed for 40–70 min after receiving classroom instruction on oxidation–reduction reactions and electrochemistry. The participants were randomly assigned via coin toss to one of two groups—one group (N = 26) viewed the more simplified animation before viewing the more complex animation while the other group (N = 29) viewed the more complex animation before the more simplified animation.Computer animationsThe more simplified animation of the silver–copper reaction was created by the second author (Fig. 1a). This program was animated as two-dimensional such that when two objects approached each other, they were animated as colliding andbouncing off one another. The total viewing time for this animation is about 30 s; this animation was shown to the participants without narration. The animation shows coppercoloured circles in an organized pattern (copper metal) placed against a blue background (water). In the blue background, several silver-coloured circles with a ‘+’ symbol (silver ions) and an equal number of blue/red atom clusters with a ‘’ symbol on it (nitrate ions) move freely. As the reaction occurs, two silver circles approach a copper circle, and a red ‘e’ (electron) is transferred from the copper circle to each of the two silver circles. When the ‘e’ are transferred, the copper ci
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Pengantar
peneliti pendidikan kimia tertarik dalam mengevaluasi dan meningkatkan siswa 'kemampuan untuk memvisualisasikan fenomena kimia di tingkat partikulat telah menunjukkan bahwa penggunaan animasi komputer yang menggambarkan proses kimia pada tingkat partikulat dapat meningkatkan kimia siswa keterampilan visualisasi (Williamson dan Abraham, 1995; Russell et al, 1997;. Sanger dan Greenbowe, 2000;. Sanger et al, 2000, 2001, 2007; Sanger dan Badger, 2001; Ardac dan Akaygun, 2004;. Kelly et al, 2004; Vela'zquez-Marcano dkk. 2004; Tasker dan Dalton, 2006; Kelly dan Jones, 2007, 2008;. Gregorius et al, 2010a, 2010b; Rosenthal dan Sanger, 2012, 2013a, 2013b;.. Williamson et al, 2012)
Sebagian besar penelitian ini menggunakan ini partikulat tingkat komputer
animasi sebagai bagian dari intervensi instruksional yang dirancang untuk meningkatkan pemahaman konseptual siswa dari fenomena kimia. Penelitian ini merupakan salah satu dari sejumlah berkembang bahwa telah mulai menggunakan animasi ini sebagai bagian dari proses penilaian (Sanger et al, 2007;. Naah dan Sanger, 2012, 2013; Rosenthal dan Sanger, 2012, 2013a, 2013b). Rosenthal dan Sanger (2013a) dibandingkan penjelasan partikulat dari reaksi oksidasi-reduksi yang melibatkan logam tembaga dan larutan perak nitrat encer dari dua kelompok siswa yang telah melihat demonstrasi reaksi kimia ini dan salah satu dari dua animasi komputer partikulat-tingkat yang berbeda dari reaksi ini. Dua animasi menggambarkan reaksi kimia yang sama, namun berbeda dalam tingkat kompleksitas dari gambar visual yang digunakan dalam animasi ini. Animasi yang diciptakan oleh Michael J. Sanger (disebut sebagai
'lebih disederhanakan animasi') menggunakan sudut kamera statis, tidak menggambarkan molekul air dalam larutan, dan digambarkan benda bergerak dan bertabrakan di satu pesawat. Animasi dibuat sebagai bagian dari proyek VisChem (Tasker dan Dalton, 2006), dan disebut sebagai 'animasi yang lebih kompleks', menggunakan mengubah sudut kamera, solusi, dan benda-benda diizinkan untuk bergerak di depan atau di belakang satu sama lain. Studi ini menunjukkan bahwa siswa melihat animasi yang lebih sederhana memberikan penjelasan yang lebih baik selama delapan konsep yang berbeda terkait dengan reaksi oksidasi-reduksi dibandingkan dengan siswa melihat animasi yang lebih kompleks.
Siswa melihat animasi yang lebih sederhana juga disediakan persamaan kimia yang seimbang lebih akurat untuk reaksi ini dibandingkan dengan siswa melihat animasi yang lebih kompleks. Kutipan dari siswa pada kedua kelompok menunjukkan bahwa mereka melihat animasi yang lebih kompleks underperformed dibandingkan dengan mereka melihat animasi yang lebih sederhana karena themore animasi kompleks digambarkan informasi asing dan baik tidak menggambarkan informasi yang relevan atau informasi yang relevan digambarkan bahwa sulit bagi siswa untuk melihat karena efek merugikan dari informasi asing. Dalam sebuah studi tindak lanjut, Rosenthal dan Sanger (2013b) dibandingkan bagaimana urutan melihat dua animasi yang berbeda dari nitrat tembaga-perak reaksi oksidasi-reduksi dipengaruhi penjelasan partikulat-tingkat siswa dari reaksi ini. Mereka menemukan bahwa siswa yang melihat semakin kompleks
animasi diikuti oleh animasi yang lebih sederhana memberikan penjelasan yang lebih baik selama tujuh konsep dan memberikan persamaan kimia yang seimbang lebih benar daripada mereka siswa yang melihat animasi dalam urutan terbalik. Siswa yang disukai menunjukkan animasi yang lebih kompleks diikuti oleh animasi lebih disederhanakan percaya bahwa animasi yang lebih kompleks akan mendapatkan perhatian siswa (oleh menghibur atau membingungkan mereka), dan kemudian animasi yang lebih sederhana akan lebih jelas menjelaskan apa yang terjadi dalam reaksi, yang menyebabkan peningkatan pembelajaran. Namun, interpretasi hasil dari penelitian ini dipersulit oleh kenyataan bahwa banyak dari penjelasan siswa yang langsung terkait dengan versi animasi mereka melihat, dan perbedaan dalam penjelasan mereka mungkin merupakan artefak dari animasi terakhir dilihat . dan tidak harus urutan di mana dua animasi dipandang
Salah satu kesimpulan dari studi terakhir ini (Rosenthal dan Sanger, 2013b) adalah bahwa melihat animasi lebih disederhanakan menjabat sebagai isyarat instruksional (Mayer dan Gallini, 1990; Patrick dkk ., 2005; Mayer dan Wittrock, 2009; Masak et al, 2011;. Lin
dan Atkinson, 2011) bahwa siswa dibantu dalam menafsirkan animasi yang lebih kompleks. Namun, pernyataan ini tidak secara khusus diuji dalam penelitian itu. Tujuan dari penelitian ini adalah untuk menentukan bagaimana melihat salah satu animasi mempengaruhi
penjelasan selanjutnya peserta dari animasi lainnya. Kerangka teori
Ketika menjelaskan fenomena kimia, ahli kimia sering menggunakan tiga terkait tetapi berbeda representasional tingkat-makroskopik, partikulat, dan tingkat simbolik (Johnstone, 1993; Gilbert dan Treagust, 2009; Johnstone, 2010; Talanquer,
2011). Representasi makroskopik melibatkan pengamatan kualitatif fenomena kimia yang dibuat menggunakan panca indera (perubahan warna, bau, perubahan panas, dll), representasi partikulat melibatkan perilaku atom, molekul, dan
ion yang terlibat dalam fenomena kimia, dan representasi simbolik melibatkan simbol-simbol digunakan (angka, rumus matematika, simbol kimia dan rumus, persamaan yang seimbang, dll) untuk mewakili konsep yang lebih abstrak.
Efektivitas menggunakan animasi komputer dari proses kimia pada tingkat partikulat didasarkan pada teori kognitif Mayer multimedia pembelajaran ( Mayer, 2001), yang diadaptasi dari dual-coding teori Paivio ini (Paivio, 1986) dan model Baddeley tentang memori kerja (Baddeley, 1986). Teori Mayer mengasumsikan bahwa peserta didik memiliki saluran kognitif terpisah untuk memproses visual (bergambar) dan pendengaran (verbal) informasi, bahwa peserta didik memiliki kemampuan pemrosesan terbatas di masing-masing saluran, dan bahwa peserta didik terlibat dalam pembelajaran aktif dengan memperhatikan informasi yang relevan, mengorganisir informasi ini ke jiwa . skema, dan mengintegrasikan pengetahuan baru ini dengan yang sudah ada pengetahuan
teori Mayer pembelajaran multimedia menggabungkan teori beban kognitif (Baddeley, 1986; Sweller, 1994; Sweller dan Chandler, 1994), yang mengasumsikan bahwa peserta didik telah memori kerja dan terbatas panjang terbatas memori-istilah. Jika beban kognitif pelajaran instruksional melebihi batas memori kerja pelajar, maka belajar akan terhambat atau berkurang. Ada dua jenis beban kognitif yang mempengaruhi belajar (Sweller, 1994; Sweller dan Chandler, 1994). Beban kognitif intrinsik adalah properti dari konten yang harus dipelajari; konsep yang dapat diproses secara berurutan dan secara independen satu sama lain merupakan beban intrinsik rendah, sementara konsep yang harus diproses secara bersamaan merupakan beban intrinsik yang lebih tinggi. Beban kognitif asing, di sisi lain, adalah fungsi dari bagaimana materi pembelajaran disajikan. Karena cara pelajaran disajikan tidak mengubah konten yang akan dipelajari, setiap beban kognitif asing dikenakan oleh cara di mana pelajaran disajikan menggunakan sumber daya kognitif tanpa meningkatkan pembelajaran (Lee et al., 2006).
Oleh karena itu, tujuan desain pembelajaran adalah untuk mengurangi beban kognitif asing dengan memanipulasi verbal (teks dan narasi) dan informasi bergambar. Sebagai contoh, Mayer (2001) memberikan tujuh prinsip desain multimedia untuk meminimalkan beban kognitif asing berdasarkan hasil beberapa studi penelitian pendidikan. Peneliti lain (Lee et al, 2006;. Homer dan Plass, 2010) telah menunjukkan bahwa menambahkan informasi ikon untuk visual simbolik yang digunakan dalam animasi komputer dapat meningkatkan belajar siswa dengan meminimalkan beban kognitif yang asing. Visual simbolik menggunakan representasi sewenang-wenang untuk menggambarkan suatu objek atau konsep, sedangkan visual ikonik menggunakan representasi yang terkait dengan objek atau konsep oleh hubungan permukaan-tingkat (misalnya, ketika menggambarkan sebuah objek yang dipanaskan, menggunakan slide bar dengan kata 'Suhu' di atas itu merupakan visual simbolik; menunjukkan penambahan atau penghapusan pembakar Bunsen bawah objek yang dipanaskan atau didinginkan mewakili visual ikon). Para peneliti telah menunjukkan bahwa efek positif dari memberikan informasi ikon yang terbesar ketika siswa memiliki pengetahuan sebelumnya rendah dan ketika konsep-konsep yang sangat kompleks (Lee et al, 2006;. Kalyuga, 2007; Homer dan Plass, 2010). Metodologi
Subyek
Sampel terdiri dari 55 siswa relawan (19 laki-laki dan 36 perempuan) terdaftar di bagian yang sama dari kursus kimia pengantar kedua semester dimaksudkan untuk kimia, biologi, dan ilmu kesehatan dan jurusan yang diajarkan oleh instruktur kimia yang sama. Setiap peserta diwawancarai untuk 40-70 menit setelah menerima instruksi kelas pada reaksi oksidasi-reduksi dan elektrokimia. Para peserta secara acak melalui lemparan koin ke salah satu dari dua kelompok-satu kelompok (N = 26) dilihat animasi lebih disederhanakan sebelum melihat animasi yang lebih kompleks sedangkan kelompok lainnya (N = 29) dilihat animasi yang lebih kompleks sebelum lebih disederhanakan animasi.
Komputer animasi
The animasi yang lebih sederhana dari reaksi perak-tembaga diciptakan oleh penulis kedua (Gambar. 1a). Program ini animasi sebagai dua dimensi seperti ketika dua benda mendekati satu sama lain, mereka animasi sebagai bertabrakan dan
memantul dari satu sama lain. Total waktu menonton animasi ini adalah sekitar 30 s; animasi ini ditunjukkan kepada peserta tanpa narasi. Menunjukkan animasi coppercoloured lingkaran dalam pola terorganisir (logam tembaga) ditempatkan dengan latar belakang biru (air). Dalam latar belakang biru, beberapa kalangan berwarna perak dengan '+' simbol (ion perak) dan jumlah yang sama dari biru / cluster atom merah dengan '?' simbol di atasnya (ion nitrat) bergerak bebas. Sebagai reaksi terjadi, dua lingkaran perak mendekati lingkaran tembaga, dan merah 'e?' (elektron) ditransfer dari lingkaran tembaga untuk masing-masing dua lingkaran perak. Ketika 'e?' ditransfer, ci tembaga
peneliti pendidikan kimia tertarik dalam mengevaluasi dan meningkatkan siswa 'kemampuan untuk memvisualisasikan fenomena kimia di tingkat partikulat telah menunjukkan bahwa penggunaan animasi komputer yang menggambarkan proses kimia pada tingkat partikulat dapat meningkatkan kimia siswa keterampilan visualisasi (Williamson dan Abraham, 1995; Russell et al, 1997;. Sanger dan Greenbowe, 2000;. Sanger et al, 2000, 2001, 2007; Sanger dan Badger, 2001; Ardac dan Akaygun, 2004;. Kelly et al, 2004; Vela'zquez-Marcano dkk. 2004; Tasker dan Dalton, 2006; Kelly dan Jones, 2007, 2008;. Gregorius et al, 2010a, 2010b; Rosenthal dan Sanger, 2012, 2013a, 2013b;.. Williamson et al, 2012)
Sebagian besar penelitian ini menggunakan ini partikulat tingkat komputer
animasi sebagai bagian dari intervensi instruksional yang dirancang untuk meningkatkan pemahaman konseptual siswa dari fenomena kimia. Penelitian ini merupakan salah satu dari sejumlah berkembang bahwa telah mulai menggunakan animasi ini sebagai bagian dari proses penilaian (Sanger et al, 2007;. Naah dan Sanger, 2012, 2013; Rosenthal dan Sanger, 2012, 2013a, 2013b). Rosenthal dan Sanger (2013a) dibandingkan penjelasan partikulat dari reaksi oksidasi-reduksi yang melibatkan logam tembaga dan larutan perak nitrat encer dari dua kelompok siswa yang telah melihat demonstrasi reaksi kimia ini dan salah satu dari dua animasi komputer partikulat-tingkat yang berbeda dari reaksi ini. Dua animasi menggambarkan reaksi kimia yang sama, namun berbeda dalam tingkat kompleksitas dari gambar visual yang digunakan dalam animasi ini. Animasi yang diciptakan oleh Michael J. Sanger (disebut sebagai
'lebih disederhanakan animasi') menggunakan sudut kamera statis, tidak menggambarkan molekul air dalam larutan, dan digambarkan benda bergerak dan bertabrakan di satu pesawat. Animasi dibuat sebagai bagian dari proyek VisChem (Tasker dan Dalton, 2006), dan disebut sebagai 'animasi yang lebih kompleks', menggunakan mengubah sudut kamera, solusi, dan benda-benda diizinkan untuk bergerak di depan atau di belakang satu sama lain. Studi ini menunjukkan bahwa siswa melihat animasi yang lebih sederhana memberikan penjelasan yang lebih baik selama delapan konsep yang berbeda terkait dengan reaksi oksidasi-reduksi dibandingkan dengan siswa melihat animasi yang lebih kompleks.
Siswa melihat animasi yang lebih sederhana juga disediakan persamaan kimia yang seimbang lebih akurat untuk reaksi ini dibandingkan dengan siswa melihat animasi yang lebih kompleks. Kutipan dari siswa pada kedua kelompok menunjukkan bahwa mereka melihat animasi yang lebih kompleks underperformed dibandingkan dengan mereka melihat animasi yang lebih sederhana karena themore animasi kompleks digambarkan informasi asing dan baik tidak menggambarkan informasi yang relevan atau informasi yang relevan digambarkan bahwa sulit bagi siswa untuk melihat karena efek merugikan dari informasi asing. Dalam sebuah studi tindak lanjut, Rosenthal dan Sanger (2013b) dibandingkan bagaimana urutan melihat dua animasi yang berbeda dari nitrat tembaga-perak reaksi oksidasi-reduksi dipengaruhi penjelasan partikulat-tingkat siswa dari reaksi ini. Mereka menemukan bahwa siswa yang melihat semakin kompleks
animasi diikuti oleh animasi yang lebih sederhana memberikan penjelasan yang lebih baik selama tujuh konsep dan memberikan persamaan kimia yang seimbang lebih benar daripada mereka siswa yang melihat animasi dalam urutan terbalik. Siswa yang disukai menunjukkan animasi yang lebih kompleks diikuti oleh animasi lebih disederhanakan percaya bahwa animasi yang lebih kompleks akan mendapatkan perhatian siswa (oleh menghibur atau membingungkan mereka), dan kemudian animasi yang lebih sederhana akan lebih jelas menjelaskan apa yang terjadi dalam reaksi, yang menyebabkan peningkatan pembelajaran. Namun, interpretasi hasil dari penelitian ini dipersulit oleh kenyataan bahwa banyak dari penjelasan siswa yang langsung terkait dengan versi animasi mereka melihat, dan perbedaan dalam penjelasan mereka mungkin merupakan artefak dari animasi terakhir dilihat . dan tidak harus urutan di mana dua animasi dipandang
Salah satu kesimpulan dari studi terakhir ini (Rosenthal dan Sanger, 2013b) adalah bahwa melihat animasi lebih disederhanakan menjabat sebagai isyarat instruksional (Mayer dan Gallini, 1990; Patrick dkk ., 2005; Mayer dan Wittrock, 2009; Masak et al, 2011;. Lin
dan Atkinson, 2011) bahwa siswa dibantu dalam menafsirkan animasi yang lebih kompleks. Namun, pernyataan ini tidak secara khusus diuji dalam penelitian itu. Tujuan dari penelitian ini adalah untuk menentukan bagaimana melihat salah satu animasi mempengaruhi
penjelasan selanjutnya peserta dari animasi lainnya. Kerangka teori
Ketika menjelaskan fenomena kimia, ahli kimia sering menggunakan tiga terkait tetapi berbeda representasional tingkat-makroskopik, partikulat, dan tingkat simbolik (Johnstone, 1993; Gilbert dan Treagust, 2009; Johnstone, 2010; Talanquer,
2011). Representasi makroskopik melibatkan pengamatan kualitatif fenomena kimia yang dibuat menggunakan panca indera (perubahan warna, bau, perubahan panas, dll), representasi partikulat melibatkan perilaku atom, molekul, dan
ion yang terlibat dalam fenomena kimia, dan representasi simbolik melibatkan simbol-simbol digunakan (angka, rumus matematika, simbol kimia dan rumus, persamaan yang seimbang, dll) untuk mewakili konsep yang lebih abstrak.
Efektivitas menggunakan animasi komputer dari proses kimia pada tingkat partikulat didasarkan pada teori kognitif Mayer multimedia pembelajaran ( Mayer, 2001), yang diadaptasi dari dual-coding teori Paivio ini (Paivio, 1986) dan model Baddeley tentang memori kerja (Baddeley, 1986). Teori Mayer mengasumsikan bahwa peserta didik memiliki saluran kognitif terpisah untuk memproses visual (bergambar) dan pendengaran (verbal) informasi, bahwa peserta didik memiliki kemampuan pemrosesan terbatas di masing-masing saluran, dan bahwa peserta didik terlibat dalam pembelajaran aktif dengan memperhatikan informasi yang relevan, mengorganisir informasi ini ke jiwa . skema, dan mengintegrasikan pengetahuan baru ini dengan yang sudah ada pengetahuan
teori Mayer pembelajaran multimedia menggabungkan teori beban kognitif (Baddeley, 1986; Sweller, 1994; Sweller dan Chandler, 1994), yang mengasumsikan bahwa peserta didik telah memori kerja dan terbatas panjang terbatas memori-istilah. Jika beban kognitif pelajaran instruksional melebihi batas memori kerja pelajar, maka belajar akan terhambat atau berkurang. Ada dua jenis beban kognitif yang mempengaruhi belajar (Sweller, 1994; Sweller dan Chandler, 1994). Beban kognitif intrinsik adalah properti dari konten yang harus dipelajari; konsep yang dapat diproses secara berurutan dan secara independen satu sama lain merupakan beban intrinsik rendah, sementara konsep yang harus diproses secara bersamaan merupakan beban intrinsik yang lebih tinggi. Beban kognitif asing, di sisi lain, adalah fungsi dari bagaimana materi pembelajaran disajikan. Karena cara pelajaran disajikan tidak mengubah konten yang akan dipelajari, setiap beban kognitif asing dikenakan oleh cara di mana pelajaran disajikan menggunakan sumber daya kognitif tanpa meningkatkan pembelajaran (Lee et al., 2006).
Oleh karena itu, tujuan desain pembelajaran adalah untuk mengurangi beban kognitif asing dengan memanipulasi verbal (teks dan narasi) dan informasi bergambar. Sebagai contoh, Mayer (2001) memberikan tujuh prinsip desain multimedia untuk meminimalkan beban kognitif asing berdasarkan hasil beberapa studi penelitian pendidikan. Peneliti lain (Lee et al, 2006;. Homer dan Plass, 2010) telah menunjukkan bahwa menambahkan informasi ikon untuk visual simbolik yang digunakan dalam animasi komputer dapat meningkatkan belajar siswa dengan meminimalkan beban kognitif yang asing. Visual simbolik menggunakan representasi sewenang-wenang untuk menggambarkan suatu objek atau konsep, sedangkan visual ikonik menggunakan representasi yang terkait dengan objek atau konsep oleh hubungan permukaan-tingkat (misalnya, ketika menggambarkan sebuah objek yang dipanaskan, menggunakan slide bar dengan kata 'Suhu' di atas itu merupakan visual simbolik; menunjukkan penambahan atau penghapusan pembakar Bunsen bawah objek yang dipanaskan atau didinginkan mewakili visual ikon). Para peneliti telah menunjukkan bahwa efek positif dari memberikan informasi ikon yang terbesar ketika siswa memiliki pengetahuan sebelumnya rendah dan ketika konsep-konsep yang sangat kompleks (Lee et al, 2006;. Kalyuga, 2007; Homer dan Plass, 2010). Metodologi
Subyek
Sampel terdiri dari 55 siswa relawan (19 laki-laki dan 36 perempuan) terdaftar di bagian yang sama dari kursus kimia pengantar kedua semester dimaksudkan untuk kimia, biologi, dan ilmu kesehatan dan jurusan yang diajarkan oleh instruktur kimia yang sama. Setiap peserta diwawancarai untuk 40-70 menit setelah menerima instruksi kelas pada reaksi oksidasi-reduksi dan elektrokimia. Para peserta secara acak melalui lemparan koin ke salah satu dari dua kelompok-satu kelompok (N = 26) dilihat animasi lebih disederhanakan sebelum melihat animasi yang lebih kompleks sedangkan kelompok lainnya (N = 29) dilihat animasi yang lebih kompleks sebelum lebih disederhanakan animasi.
Komputer animasi
The animasi yang lebih sederhana dari reaksi perak-tembaga diciptakan oleh penulis kedua (Gambar. 1a). Program ini animasi sebagai dua dimensi seperti ketika dua benda mendekati satu sama lain, mereka animasi sebagai bertabrakan dan
memantul dari satu sama lain. Total waktu menonton animasi ini adalah sekitar 30 s; animasi ini ditunjukkan kepada peserta tanpa narasi. Menunjukkan animasi coppercoloured lingkaran dalam pola terorganisir (logam tembaga) ditempatkan dengan latar belakang biru (air). Dalam latar belakang biru, beberapa kalangan berwarna perak dengan '+' simbol (ion perak) dan jumlah yang sama dari biru / cluster atom merah dengan '?' simbol di atasnya (ion nitrat) bergerak bebas. Sebagai reaksi terjadi, dua lingkaran perak mendekati lingkaran tembaga, dan merah 'e?' (elektron) ditransfer dari lingkaran tembaga untuk masing-masing dua lingkaran perak. Ketika 'e?' ditransfer, ci tembaga
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