The impact of multimedia effect on science learning: Evidence from eye movements

Computers & Education 53 (2009) 1297–1307

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The impact of multimedia effect on science learning: Evidence from eye movements Hsiao-Ching She *, Yi-Zen Chen Institute of Education, National Chiao Tung University, 1001 Ta-Hsueh Rd., Hsin Chu City 300, Taiwan

a r t i c l e

i n f o

Article history: Received 12 May 2009 Received in revised form 17 June 2009 Accepted 18 June 2009

Keywords: Media in education Applications in subject areas Secondary education

a b s t r a c t This study examined how middle school students constructed their understanding of the mitosis and meiosis processes at a molecular level through multimedia learning materials presented in different interaction and sensory modality modes. A two (interaction modes: animation/simulation) by two (sensory modality modes: narration/on-screen text) factorial design was employed. The dependent variables included subjects’ pre-test, post-test, and retention-test scores, showing their understanding of mitosis and meiosis process at molecular level, as well as data of subjects’ eye-movement behavior. Results showed the group that received animation with narration allocated a greater amount of visual attention (number of fixations, total inspection time, and mean fixation duration) than the group that received animation with on-screen text, in both pictorial area and area of interest, which is consistent with students’ immediate and long-term retained learning of the processes of mitosis and meiosis. The group that received simulation with on-screen text allocated a greater amount of visual attention than the group that received simulation with narration, consistent with students’ immediate and retained learning. The group that received simulation with on-screen text also allocated a greater amount of visual attention than the group that received animation with on-screen text, consistent with students’ immediate and retained learning. This study adds empirical evidence of a direct correlation between the length of eye fixation behavior and the depth of learning. Moreover, it provides insight into the multimedia effect on students’ cognitive process through the use of eye fixation behavior evidence. Ó 2009 Elsevier Ltd. All rights reserved.

1. Introduction Multimedia offers great potential as a powerful learning technology to enhance human learning. Mayer (2001) classified the multimedia presentation of materials into words and pictures. Pictures can be presented as static pictures, illustrations, graphics, animation, simulation, photos, or video. Words can be presented as on-screen text or narration. Mayer has devoted his effort on multimedia effect to studying how people learn from animation and narration vs. narration alone or from text and illustrations vs. text alone (Mayer, 1989; Mayer & Anderson, 1992; Mayer, Bove, Bryman, Mars, & Tapangco, 1996; Mayer & Moreno, 1998). These studies indicate that students who receive a multimedia lesson consisting of words and pictures perform better on a subsequent transfer test than students who received the same information in words alone. Moreover, Mayer and his colleagues conducted a series of experiments and found that subjects who received animation with concurrent narration outperformed the subjects who received animation with concurrent on-screen text. Mousavi, Low, and Sweller (1995) also found that students learned substantially better when the learning material was presented in audio–visual format than when it was presented in visual-only format. This indicates that students learn better when information is presented with multimedia, combining audio–visual formats, rather than in visual-only format. Very little research has examined this multimedia effect on simulation. Simulation is the representation of learning materials on the screen, giving the learner opportunities to learn about it through interacting with or manipulating the learning materials. Some research indicates that simulation tends to facilitate far transfer (Clark & Voogel, 1985), while other research shows students learn better and also retain the learning for a longer period (Parush, Hamm, & Shtub, 2002). However some of the research did not show a difference when compared with lab work (Kelly, 1998). We were interested in exploring whether or not presenting information through simulation would follow the multimedia effect. Therefore, we specifically designed a two (animation vs. simulation) by two factorial design (on-screen text vs. narration). Most of these studies were conducted through examining the effects of immediate or transfer learning outcome or problem solving ability. Just and Carpenter (1976a, 1976b) addressed the concept that eye-movement data can provide valuable information about the

* Corresponding author. Tel.: +886 35731665; fax: +886 35738083. E-mail address: [email protected] (H.-C. She). 0360-1315/$ - see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.compedu.2009.06.012

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cognitive process of the learner. Rayner (1998) addressed the idea that eye-movement parameters such as number of fixations, fixation duration, duration time, and scan paths are especially relevant to learning. Specifically, Underwood, Jebbett, and Roberts (2004) reported that fixation durations were longer on pictures than on sentences, which is consistent with results that recognition of words in sentences requires less processing time and shorter fixations than does the recognition of objects in pictures (Carroll, Young, & Guertin, 1992; Rayner, Rotello, Stewart, Keir, & Duffy, 2001). Hegarty (1992) indicated that subjects’ eye fixations as they read text accompanied by diagrams indicate that the comprehension of the mechanics process is largely text directed. The diagram is inspected to check or to construct the representation of information read in the text, and diagram inspection appears to be more central to representing certain types of information, in particular information about the kinematics of the system. It somehow implies that fixations are sensitive to the structure of the internal representation being constructed or operated on (Yarbus, 1967). Underwood, Templeman, Lamming, and Foulsham (2008) study provides some support that objects can be recognized prior to their fixation and this process of recognition can be used to guide future eye movements. They found that incongruent objects that violated the scene gist were fixated earlier than the objects that were consistent with the gist. The longer inspection time, greater number of fixations, and longer durations of fixations on the objects were also found when the display contained an incongruous object. All of these studies indicate a promising direction of using eye tracking to assist our understanding of the impact of multimedia on students’ cognitive process. Therefore, the eye-tracking technique was employed in this study to investigate how different multimedia instruction formats cause different cognitive learning outcomes when students are engaged in learning about mitosis and meiosis. 2. Invisible concepts of mitosis and meiosis Genetics is generally regarded as being very difficult to learn (Marbach-Ad & Stavy, 2000). In genetics instruction, students are simultaneously exposed to many new concepts and processes at the macro and molecular levels of organization simultaneously (Fisher, 1983; Kindfield, 1992). Students’ difficulties in understanding concepts and processes in genetics emerge mainly on the molecular level (molecular genetics) as a result of the emphasis on minute details and abstract concepts (Malacinski & Zell, 1996). Lewis and Wood-Robinson (2000) reported that students aged 14–16 lacked basic knowledge and understanding of the nature of genetic information, basic biological structures (such as cell, chromosome, and gene) and their relationship to each other. Many research studies have reported a variety of students’ misconceptions about the process of meiosis (Brown, 1990; Hackling & Treagust, 1984; Smith, 1991). Mixing up the functions and procedures of mitosis and meiosis (Radford & Bird-Stewart, 1982), failing to name the various phases appearing in mitosis and meiosis or being unable to arrange them in a correct sequence (Brown, 1990; Smith, 1991), and confusing the terminology for mitosis and for meiosis (Cho, Kahle, & Nordland, 1985; Longden, 1982; Pearson & Hughes, 1988) are some common misconceptions found in student thinking. The concepts of meiosis are more difficult for students to understand – that is, concepts involving DNA replication, chromosome separation, chromosome movement, and trait transmission (Johnstone & Mahmound, 1980). Students may not be aware of the relationships among the basic concepts of meiosis and genetics. They have difficulty understanding why the process of mitosis only goes through chromosome replication and separation once, while meiosis goes through chromosome replication once and separation twice. Students are very confused about when and why sister chromatids and homologous chromosomes separate. Particularly, students are confused about when and how chromosomes doubled to formed chromatids from each of the homologous chromosomes. They also have difficulty understanding the origin of each pair of homologous chromosomes. Mitosis and meiosis describes a continuous process and provides a basis for understanding the invisible molecular events underlying natural phenomena. In order to be fully able to construct the concepts of mitosis and meiosis at the molecular level, it is very important to actually visualize or manipulate the continuous movement process. Therefore, this current study aims to design animation and simulation which will help students to construct molecular representation of mitosis and meiosis. 3. Cognitive theory of multimedia learning The cognitive theory of multimedia learning proposed by Mayer and his colleagues (Mayer, 1997; Mayer & Moreno, 2002) is congruent with the dual coding theory (Clark & Paivio, 1991; Paivio, 1986). Dual coding theory consists of two separate subsystems for human cognition which specialize the processing of nonverbal (visual, image) and verbal (language) information. Both systems are independent; however, they are interconnected with each other, so that the activation from one representational unit to the other between systems is possible. Dual coding theory suggests that learning is enhanced when complementary information codes are received simultaneously, such as a combination of visual and auditory information. Mayer (2002) addressed the idea that humans possess separate information processing channels for visually represented material and auditory represented material. When information is presented to the eyes (such as illustrations, animation, video, or on-screen text), humans process the information in the visual channel; when information is presented to the ears (such as narration or nonverbal sound) then humans process that information in the auditory channel. The concept of separate information processing channels is consistent with Baddeley’s tripartite model of working memory (Baddeley, 1986, 1999). Mayer (1989) has suggested that learners who study expository text with illustration perform better than students who use only text. These studies suggest that learning can be enhanced when the instruction includes both verbal and pictorial information (Mayer, 1989; Mayer & Gallini, 1990). Learners may have difficulties when multiple sources of information, such as text and illustrations, need to be integrated at the same time. Chandler and Sweller (1992) also proposed that spatially integrating related text and pictures would solve the problem. Mousavi et al. (1995) showed that students learned better when the instructional material was presented in audio–visual format than when the material was presented in visual-only format. Mayer and Moreno (1998, 2002) conducted a series of experiments and found that subjects who received animation with concurrent narration outperformed the subjects who received animation with concurrent onscreen text. Nevertheless, some others indicate several limitations of the modality effect. Kalyuga, Chandler, and Sweller (1999) assumed that using auditory text (narration) would not be effective if the material was too long or complex, as it might overburden working memory because ‘‘auditory information is fleeting and difficult to retrieve once heard” (p. 368). In contrast, visual text (on-screen text) has the advantage of being permanent and thus can be referred to repeatedly. Tabbers, Martens, and van Merrienboer (2004) even found a reversed modality effect whereby students actually learned less effectively with audio–visual materials.

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Simulations are recognized as a potential, efficient, and effective strategy of teaching and learning complex and dynamic conceptions. Simulation is the representation of learning materials on the screen, giving the learner opportunities to learn through interacting with, or manipulating, the material. Studies point out that simulation can foster critical thinking, problem solving skills, the asking of more ‘‘what if” questions, and more inquiry learning (Baggott & Nichol, 1998; Boyle, 2004; Linn, 2004). Some research indicates that simulation tends to facilitate far transfer (Clark & Voogel, 1985) and improve students cognitive gain after learning from physical simulation (Yildiz & Atkins, 1996), others show students learn better and also retain the learning after for a period of learning (Parush et al., 2002). Some of the research did not show a difference in comparison with lab work (Kelly, 1998). The multimedia effect on simulation is rarely examined, thus we would be interested in examining it as well. 4. Eye-movements and cognitive process Eye movements can reveal a great deal about underlying cognitive processes (Just & Carpenter, 1984; Rayner, 1995, 1998). The eyemind hypothesis states that there is a strong correlation between where one is looking and what one is thinking about (Just & Carpenter, 1984). They point out a linkage between eye fixation behavior (locus, duration and sequence) and a cognitive processing model for both graphic and textual visual materials (Just & Carpenter, 1976a, 1976b). Rayner further point out that longer fixation durations are generally indicative of more extensive processing (Rayner, 1998), and reflect a difficulty such as the encountering of a word of low frequency (e.g. Rayner & Duffy, 1986) or a word that is contextually implausible (Ehrlich & Rayner, 1981). Other research indicated that the longer mean fixation duration is associated with better transfer performance (Ozcelik, Karakus, Kursun, & Cagiltay, 2009). For explaining the parameters of eye movements, Rayner (1998) suggested eye-movement parameters such as number of fixations, mean fixation duration and total inspection time are especially relevant to learning. Several researches specifically addressed the characteristics of eye movements when text and pictures have to be integrated in the comprehension process. Underwood et al. (2004) reported that fixation durations were longer on pictures than on sentences for both the cases of concurrent displays the sentence with pictures or when sentences preceded picture. On contrary, when the sentence can be read first then inspecting the picture result in fewer fixations on the picture than on the scene, processing is easier when the text is read first. It is consistent with results of Carroll et al. (1992) study about how people look at cartoons consisting of a single picture and a relevant caption, and Rayner et al. (2001) study of eye movement when looking at print advertisements integrating text and pictorial information, that recognition of words in sentences requires less processing time and shorter fixations than does the recognition of objects in pictures. Hannus and Hyona (1999) used eye tracking to investigate children’s learning out of a science textbook. They found that illustration assists learning with illustrated-text content, but not that of non-illustrated-text content. The eye-movement data indicated that learning is heavily driven by the text and that children inspect illustrations only minimally. The result is different from Koran and Koran (1980) study, where the author explained that most studies examines a single picture to the text, while their study examined authentic textbook passages, all containing several illustrations, which adds to the complexity of learning materials. Other studies pointed out that eye-movement patterns are not random and learners tend to allocate greater amount of attention on areas of the scene that are considered as unusual or incongruent. Loftus and Mackworth (1978) reported that observers fixate earlier, more often, and with longer durations on objects that have a low probability of appearing in a scene than on objects that have a high probability of appearing. Underwood et al. (2008) study provides some support that a longer inspection of the display, a greater number of fixations on the display, and longer durations of fixations on the objects occur when the display contains an incongruous object. Some studies have further reported that memory for a scene was related to the number of fixations made on the scene, and more fixations yield higher recognition scores (Christianson, Loftus, Hoffman, & Loftus, 1991; Loftus, 1972). Moreover, eye movements have been recorded as participants solve math and physics problems and it was found that more complicated aspects of the problem typically lead to more and longer fixations (Hegarty & Just, 1993; Hegarty, Mayer, & Green, 1992). Though many studies have examined the pattern of human eye movement while viewing text with picture information, but there is a lack of studies using the cognitive techniques in assisting our understanding of the multimedia effect. Thus, we attempted to investigate the effects of presentation modes (animation with narration vs. animation with on-screen text vs. simulation with narration vs. simulation vs. on-screen text) of multimedia learning material on students’ mitosis and meiosis learning process and performance. The eye-tracking technique was used to tackle the tacit cognitive processes underlying learning, i.e. studying how students allocate their attention to different sources of information during learning. Moreover, we administrated pre-, post- and retention-tests to find out the learning outcome. 5. Method 5.1. Design A two (sensory modality modes: narration/on-screen text) by two (interaction modes: animation/simulation) factorial design was employed. The dependent variables included subjects’ pre-test, post-test, and retention-test scores concerning their understanding of the mitosis and meiosis process at a molecular level as well as data regarding subjects’ eye-movement behavior, such as (1) the average length of viewing time (total inspection time), (2) the average number of fixations (number of fixations) and (3) the average length of time of a fixation (mean fixation duration). The mitosis process consists of four stages: stage 1 chromosome replication, stage 2 alignment of duplicate chromosome sets in the center of cell, stage 3 duplicated chromosomes split and sister chromatids are pulled to the opposite of the cell, and stage 4 one cell divided into two separate cells (Fig. 1). The meiosis process consists of four stages: stage 1 chromosome replication, stage 2 first division which separates the homologous pairs of chromosomes and forms two cells, stage 3 second division which separates sister chromatids, and stage 4 cell wall formation which results in four haploid daughter cells (Fig. 2). Both mitosis and meiosis occur in a rapid continual process. The process of mitosis and meiosis is a continuous process; therefore, it is necessary to present them as a continual process. An animation can be defined as a series of rapidly changing computer screen displays suggesting movement to the viewer (Rieber & Kini, 1991). The instruction accompanying the animation regarding mitosis conveyed how a cell starts mitosis and how the number, format, and movement

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Fig. 1. Continuous process of mitosis.

Fig. 2. Continuous process of meiosis.

of chromosomes change at each stage and become two identical cells throughout the mitosis process. The instruction accompanying the animation regarding meiosis conveyed how a cell starts meiosis and how the number, format and movement of chromosome change at each stage and become four cells. The instruction accompanying the simulation was presented in an interactive way, allowing students to manipulate when, whether and how many times a chromosome would duplicate or separate. Simulation is an attempt to model a real-life or hypothetical situation on a computer. In this case the simulation allowed students to see how the mitosis or meiosis process works. By changing variables of the number and timing of replication or separation, predictions can be made about the behavior of the system. For the instruction accompanying the animation, the same materials as simulation were presented. The same materials used in the simulation were included in the instruction accompanying the animation. This time, however, they were presented in a non-interactive way, which means students are not able to manipulate and interact with the mitosis and meiosis process. The sensory modality modes were employed to display the instructions: narration and on-screen text format. The narration and onscreen text format of instruction explained the process of mitosis and meiosis, while the same explanations were presented in text form or spoken form. In this study, those eye-movement data were collected for the pictorial area and area of interest. Furthermore, we collected eyemovement data on the area of interest (Fig. 3) concerning the changes of chromosome during the mitosis and meiosis process. The area

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Fig. 3. Area of interest (three rectangles) at the stage of alignment of chromosome at the center of cell.

of interest was chosen to examine if or how the participants paid specific attention to the changes of number, format, and movement of chromosomes in these regions. 5.2. Participants A total of twenty-four 7th grade students with an average age of 12, from four different classes at a middle school, were involved in this study. In order to avoid confounding variables of gender and achieving level on learning of four different formats of instructions, six students were selected from each class according to their biology achievement score and gender, which are: high achieving boy, high achieving girl, medium achieving boy, medium achieving girl, low achieving boy and low achieving girl, respectively. Students’ first semester’s biology average scores were used to differentiate students into high, medium and low achieving students. Each class of six students received only one format of displaying instruction: animation-text, animation-narration, simulation-text, or simulation-narration, respectively. 5.3. Procedures All of the 24 participants received the same mitosis and meiosis test before, after, and five weeks after learning the multimedia learning material involving the mitosis and meiosis process. The four different presentations of the mitosis and meiosis learning materials were animation-narration, animation-text, simulation-narration, and simulation-text. Students were assigned into four different presentation modes according to class. Each group of six students received one presentation of multimedia learning materials, which they learned by computer individually at their own pace. While they were learning on the computer, their eye movements were registered by the Eye Gaze System (from LC Technologies Inc., with the sampling rate of 60 Hz). 5.4. Mitosis and meiosis test The mitosis and meiosis test consisted of four questions: (1) a mitosis drawing question which requested students to draw and explain the sequence of mitosis, the changes of the number, format, and movement of chromosome, and the changes of the number of cells; (2) a meiosis drawing question which requested students to draw and explain the sequence of mitosis, the changes of the number, format, and movement of chromosome, and the changes of the number of cells; (3) a two-tier mitosis question which requested students to decide which sequence was right and to choose the right reason; and (4) a two-tier meiosis question which requested students to decide which sequence was right and to choose the right reason. The purpose of this questionnaire is to assess students’ understanding of the mitosis and meiosis processes regarding the sequence of mitosis and meiosis, the changes of number and format of chromosome during mitosis and meiosis, and the resulting number of cells after the process completes. A rubric coding system was developed to measure the mitosis and meiosis drawing. One point was given for accurate chromosome changes according to each stage of mitosis, giving a maximum score of 5 points. One point was given for the number of cells produced after mitosis. One point was given for accurate chromosome changes according to each stage of meiosis, giving a maximum score of 6 points. One point was given for the number of cells produced at meiosis I and meiosis II, giving a maximum score of 2. In addition, one point was given to each two-tier question if both tiers are correct, giving a maximum score of 2 points for these two two-tier questions. Adding all of these scores gives a maximum score of 16 points for this questionnaire. Two raters were responsible for scoring subjects’ answers, with an inter-rater reliability of 0.94.

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6. Results 6.1. Analysis of mitosis and meiosis test A two factor MANCOVA was conducted to examine the effects of interaction modes and modality modes using post- and retention-test as the dependent measures, and students’ pre-test as the covariate. The result revealed an effect for the interaction between two factors on the post- and retention-test scores with a large effect size (F(1, 19) = 1.88, p = 0.181, partial g2 = 0.17). Cohen (1973), Thompson (2006) and Vacha-Haase and Thompson (2004) defined effect size as small ð0:06 > partial g2 = 0:01Þ, medium ð0:14 > partial g2 = 0:06Þ, and large ðpartial g2 = 0:14Þ. Because the interaction between two factors existed as a large effect size, a simple main effect was performed. Results indicated that the students who received animation with narration performed better than those who received animation with on-screen text on the post- and retention-test with a small and medium effect size (F(1, 9)(post) = 0.47, partial g2 = 0.049; F(1, 9)(retention) = 1.33, partial g2 = 0.129). Students who received simulation with on-screen text performed better than those who received the simulation with narration on the post-test and retention-test with a small and large effect size (F(1, 9)(post) = 0.094, partial g2 = 0.01; F(1, 9)(reten2 tion) = 1.969, p = 0.194, partial g = 0.18). Students who received on-screen text with simulation outperformed those who received onscreen text with animation (F(1, 9) (post) = 1.097, partial g2 = 0.109; F(1, 9)(retention) = 13.58, p = 0.005, partial g2 = 0.601) on post-test and retention-test and was found to be significant with large effect size. The difference was not so obvious while comparing the group who received narration with simulation to the narration with animation group on post-test and retention-test. 6.2. Eye movement in the pictorial area We first analyzed how the viewing time was distributed among the pictorial area for the students who received the four different presentation modes (narration-animation, narration-simulation, text-animation, and text-simulation). According to ANOVA with the two main factors – interaction modes (F(1, 17)(No of fixation) = 0.06; F(1, 17)(total inspection) = 0.07; F(1, 17)(mean fixation duration) = 0.27) and sensory modality modes (F(1, 17)(No of fixation) = 0.01; F(1, 17)(total inspection) = 0.41; F(1, 17)(mean fixation duration) = 0.69) were not statistically significant. The interaction between two factors on the total inspection time and mean fixation duration spent on pictorial area were statistically significant with large effect size (F(1, 17)(total inspection) = 10.73, p = 0.004, partial g2 = 0.387; F(1, 17)(mean fixation duration) = 5.98, p = 0.026, partial g2 = 0.260). Because the interaction between two factors reached a statistically significance level, thus a simple main effect was performed. Table 1 indicated that the group that received animation with narration spent more time and had longer mean fixation duration than to those who received animation with on-screen text was found to be significant with large effect size (F(1, 9)(total inspection) = 5.15, p = 0.049, partial g2 = 0.36; F(1, 9)(mean fixation duration) = 3.37, p = 0.099, partial g2 = 0.27). While the result was reversed with the simulation mode, the participants receiving on-screen text mode spent substantially more time and had a longer mean fixation duration than narration leaning mode was found to be significant with large effect size (F(1, 8)(total inspection) = 8.88, p = 0.018, partial g2 = 0.526; F(1, 8)(mean fixation duration) = 4.89, p = 0.085, partial g2 = 0.38). Students who received on-screen text with simulation spent substantially more time and had longer mean fixation duration than those who received on-screen text with animation. It was found the effect was significant with large effect size (F(1, 9)(total inspection) = 5.30, p = 0.047; partial g2 = 0.371; F(1, 9)(mean fixation duration) = 4.32, p = 0.067, partial g2 = 0.325). While the result was reversed with the narration mode, animation participants allocated longer inspection time than the simulation participants was found to be significant with a large effect size (F(1, 8)(total inspection) = 5.37, p = 0.049, partial g2 = 0.40). The pattern of animation with narration group’s total inspection time and the mean fixation duration was significant greater than that of the animation with on-screen text group, which is consistent with students’ mitosis and meiosis learning performance on both post- and retention-test (Fig. 4). The pattern of simulation with the on-screen text group’s total inspection time and mean fixation duration were significantly greater than the simulation with narration group, which is consistent with students’ mitosis and meiosis performance on the post- and retention-test (Fig. 5). The effect on total inspection time and mean fixation duration was found to be significantly greater when comparing on-screen text with simulation to the on-screen text with animation group, which is consistent with students’ mitosis and meiosis learning performance on both post- and retention-test (Fig. 6). The effect on total inspection time was found to be greater when

Table 1 Simple main effects in the pictorial area. Animation area

Number of fixations

Total inspection time

Mean fixation duration

N

Mean

SD

F

N

Mean

SD

F

N

Mean

SD

F

Animation On-screen text Narration

6 5

134.17 154.40

37.90 72.40

0.36(0.565)a ES = S(0.038)b

6 5

24729.00 38790.20

9369.00 11214.16

5.15** (0.049)a ES = L(0.364)b

6 5

187.41 298.95

49.78 139.74

3.37* (0.099)a ES = L(0.273)b

Simulation On-screen text Narration

5 5

147.40 131.40

44.04 21.55

0.53(0.486)a ES = M(0.062)b

5 5

35563.80 26100.20

5117.76 4925.29

8.88** (0.018)a ES = L(0.526)b

5 5

252.91 197.89

54.68 10.18

4.89* (0.085)a ES = L(0.379)b

On-screen text Simulation Animation

5 6

147.40 134.17

44.04 37.90

0.29(0.605)a ES = S(0.031)b

5 6

35563.80 24729.00

5117.76 9369.00

5.30** (0.047)a ES = L(0.371) b

5 6

252.91 187.41

54.68 49.78

4.32* (0.067)a ES = L(0.325)b

Narration Simulation Animation

5 5

131.40 154.40

21.55 72.40

0.46(0.515)a ES = S(0.055)b

5 5

26100.20 38790.20

4925.29 11214.16

5.37** (0.049)a ES = L(0.402) b

5 5

197.89 298.95

10.18 139.74

2.60(0.145)a ES = L(0.245)b

a b

Sig: p 50:05; p 50:1. Partial eta: ES = effect size, large (L): ES50:14, medium (M): 0.14 > ES > 0.06, small (S): 0.06 > ES > 0.01.

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180

Number of Fixation

40000

Total inspection time

360

150

34000

300

120

28000

240

90

22000

180

60

16000

120

30

10000

60

0

4000

0

120

animation- animationtext narration

animation- animationtext narration Pictorial area

animation- animationtext narration Pictorial area

Number of Fixation

36000

Mean Fixation Duration

Total inspection time

Pictorial area

360

Mean Fixation Duration

animation-text animation-narration 12

100

30000

300

10

80

24000

240

60

18000

180

8

40

12000

120

20

6000

60

0

0

4 2

0 animation- animationtext narration Area of interest

animation- animationtext narration Area of interest

animation- animationtext narration Area of interest

6

0 Post-test

Retention-test

Fig. 4. The eye-movement data in the pictorial area and area of interest and learning outcome comparing a with animation with on-screen text vs. animation with narration.

180

Number of Fixation

36000

Total inspection time

300

150

30000

250

120

24000

200

90

18000

150

60

12000

100

30

6000

50

0

0

120

Number of Fixation

0 simulation- simulationtext narration Pictorial area

simulation- simulationtext narration Pictorial area

26000

Mean Fixation Duration

Total inspection time

simulation- simulationtext narration Pictorial area

300

Mean Fixation Duration

simulation-text simulation-narration 12

100

22000

250

10

80

18000

200

60

14000

150

8

40

10000

100

20

6000

50

0

2000

0

simulation- simulationtext narration

Area of interest

simulation- simulationtext narration Area of interest

6 4 2 simulation- simulationtext narration

0 Post-test

Retention-test

Area of interest

Fig. 5. The eye-movement data in the pictorial area and area of interest and learning outcome comparing simulation with on-screen text vs. simulation with narration.

comparing narration with animation to the narration with simulation group, while the difference of learning performance was not so obvious between two groups. 6.3. Eye movement in the area of interest The eye-movement data were collected for examining whether the participants paid specific attention to the number and structure of chromosome change in the area of interest in the pictorial area. According to ANOVA with the two main factors – interaction modes

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(F(1, 17)(No of fixation) = 0.09; F(1, 17)(total inspection) = 0.001; F(1, 17)(mean fixation duration) = 0.45) and sensory modality modes (F(1, 17)(No of fixation) = 2.72; F(1, 17)(total inspection) = 4.10, p = 0.059; F(1, 17)(mean fixation duration) = 0.45) were not significant with the exception of total inspection time for sensory modality mode. The interaction between two factors on the total inspection time and mean fixation duration spent on the area of interest were statistically significant with large effect size (F(1, 17) = 11.35, p = 0.004, partial g2 = 0.40; F(1, 17) = 6.31, p = 0.022, partial g2 = 0.271). Because the interaction between two factors was significant, the simple main effect was performed in the following. Table 2 indicated that the students who received the animation mode with narration spent substantially more time than the students who received animation with on-screen text. This was significant with a large effect size (F(1, 9)(total inspection) = 11.11, p = 0.009, partial g2 = 0.55). While the result was reversed with the simulation modes, the on-screen text participants had longer mean fixation duration than those who received narration. This was found to be significant with a large effect size (F(1, 8)(mean fixation duration) = 7.97, p = 0.022, partial g2 = 0.50). Of the students who received on-screen text modes, the simulation participants had longer mean fixation duration and spent substantially greater amount of time than those who received animation (F(1, 9)(total inspection) = 9.75, p = 0.012, partial g2 = 0.52; F(1, 9)(mean fixation duration) = 3.71, p = 0.086, partial g2 = 0.29) and were found to be significant with large effect size. The result was reversed

180

Number of Fixation

36000

Total inspection time

300

150

30000

250

120

24000

200

90

18000

150

60

12000

100

30

6000

50

0

0

0 texttextsimulation animation

texttextsimulation animation

textsimulation

Pictorial area

Pictorial area

120

Mean Fixation Duration

Number of Fixation

30000

Total inspection time

textanimation

Pictorial area

300

text-simulation

Mean Fixation Duration

12

100

25000

250

10

80

20000

200

60

15000

150

8

40

10000

100

20

5000

50

0

0

0

textsimulation

6 4 2

texttextsimulation animation

textanimation

textsimulation

Area of interest

Area of interest

text-animation

0

textanimation

Post-test

Retention-test

Area of interest

Fig. 6. The eye-movement data in the pictorial area and area of interest and learning outcome comparing the group who received animation with on-screen text with animation vs. on-screen text with simulation.

Table 2 Simple main effects in the area of interest. Number of fixation

Total inspection time

Mean fixation duration

Mean

SD

F

Mean

SD

F

Animation On-screen text Narration

76.50 122.00

17.56 60.83

3.11 (0.112)a ES = L(0.257) b

15332.00 32185.00

6504.13 10196.69

11.11*** (0.009) ES = L (0.553) b

Simulation On-screen text Narration

100.20 107.80

26.19 31.40

0.17 (0.689)a ES = S(0.021) b

25752.20 21551.20

3929.33 6653.58

1.48 (0.259)a ES = L(0.156) b

On-screen text Simulation Animation

100.20 76.50

26.19 17.56

3.22 (0.106)a ES = L(0.263) b

25752.20 15332.00

3929.33 6504.13

9.75** (0.012) ES = L(0.520) b

Narration Simulation Animation

107.80 122.00

31.40 60.83

0.22 (0.655)a ES = S(0.026) b

21551.20 32185.00

6653.58 10196.69

3.81* (0.087)a ES = L(0.323) b

a b

Sig: p 50:01; p 50:05; p 50:1. Partial eta: ES = effect size, large (L): ES50:14, medium (M): 0.14 > ES > 0.06, small (S): 0.06 > ES > 0.01.

a

a

Mean

SD

F

199.13 314.74

61.08 147.64

3.10 (0.112)a ES = L (0.256)

265.98 199.12

52.24 8.88

7.96** (0.022) a ES = L(0.499) b

265.98 199.13

52.24 61.08

3.71* (0.086)a ES = L (0.292) b

199.12 314.74

8.88 147.64

3.06 (0.119)a ES = L(0.276) b

b

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with the narration mode, where animation participants spent substantially greater amount of time than those who received simulation and was significant with a large effect size (F(1, 8)(total inspection) = 3.81, p = 0.087, partial g2 = 0.32). Fig. 4 indicates that the pattern of animation with narration group’s total inspection time in the area of interest was greater than that of the animation with on-screen text group. This is consistent with students’ eye movement in the pictorial area and students’ mitosis and meiosis learning performance on both post- and retention-test. Fig. 5 shows that the pattern of simulation with the on-screen text group’s mean fixation duration in the area of interest was significantly greater than that of the simulation with narration group. This is consistent with students’ eye-movement pattern in the pictorial area and students’ mitosis and meiosis performance on post- and retention-test. Fig. 6 shows that the pattern of simulation with on-screen text group’s total inspection time and mean fixation duration in the area of interest was greater than the animation with on-screen text group, which is consistent with students’ eye movement in the pictorial area and students’ mitosis and meiosis learning performance on both post- and retention-test. The effect on total inspection time in the area of interest was found to be greater when comparing the narration with animation group to the narration with simulation group, which is consistent with students’ eye movement in the pictorial area, while the difference in learning mitosis and meiosis was not so obvious between the two groups.

7. Conclusions and discussions Results on the interaction between sensory modality modes and interaction modes are effective on students’ understanding of the mitosis and meiosis process at a molecular level (post- and retention-scores) as well as their eye-tracking results in both the pictorial area and the area of interest. These results indicate that there is a consistent trend among the students’ understanding of the mitosis and meiosis process, eye-movement data in the pictorial area, and the area of interest. Therefore, four parts of conclusions will be discussed in the following, based upon the results from cognitive learning outcomes as well as eye-tracking results. For the animation presentation mode, the narration participants allocated a greater amount of visual attention in the pictorial area and area of interest than the group that received on-screen text, consistent with students’ immediate and retained learning of mitosis and meiosis. The result fully supports multimedia effect, or the so-called modality effect (Mayer, 1989, 2002; Mayer & Moreno, 1998, 2002; Mousavi et al., 1995), which states that people learn better from animation with narration than with from on-screen text. Our results also confirmed the linkage between eye-movement behavior (number of fixation, total inspection time, and mean fixation duration) and cognitive process (Carroll et al., 1992; Hegarty et al., 1992; Rayner, 1998). Particularly, our study moved one step beyond multimedia effect studies by adding an eye-movement behavior empirical study, which demonstrated that the animation-narration group’s students, who allocated a greater number of fixations, total inspection time and mean fixation duration in the pictorial area and area of interest, resulted in better learning performance on mitosis and meiosis than when compared to the animation-text group’s students. For the simulation presentation mode, the on-screen text participants allocated a significantly greater amount of visual attention in the pictorial area and area of interest than the narration participants, which is consistent with their post-test and retention-test scores on the mitosis and meiosis process. Previous studies suggested that comprehension process is text directed, which means text that would be read first then picture would be inspected in order to check or construct the representing of information, though picture or diagram inspection appears to be more central for comprehension process (Hegarty, 1992; Underwood et al., 2004). Based upon their report, it was reasonable for us to make an assumption that the simulation with on-screen text group would allocate a reasonable amount of attention to the onscreen text and a smaller amount of attention to the pictorial area and area of interest than would the simulation with narration group. However, our results did not support such an assumption. On the contrary, the simulation with on-screen text group allocated a significantly greater amount of attention to the pictorial area and area of interest than the simulation with narration group allocated. In addition, the immediate and retained learning result is against the multimedia effect or modality effect if we consider simulation as visual information. The possible explanations are provided in the following. Kalyuga et al. (1999) assumed that the use of auditory text (narration) would not be effective if it is too long or complex, which might overburden working memory because ‘‘auditory information is fleeting and difficult to retrieve once heard” (p. 368). In contrast, visual text (on-screen text) has the advantage of being permanent and thus can be referred to repeatedly. Meiosis and mitosis are considered to be difficult concepts for students to learn, therefore, it might be the reason why the on-screen text with simulation group spent a greater amount of time viewing the learning materials and had better learning retention than the simulation with narration group. For the on-screen text presentation mode, the simulation participants allocated a significantly greater amount of visual attention in the pictorial area and area of interest than the animation participants allocated, which is consistent with their post-test and retention-test scores on their understanding of mitosis and meiosis process at a molecular level. Our results support the idea that simulation tends to facilitate far transfer (Clark & Voogel, 1985), while others have shown that students learn better and also retain the learning (Parush et al., 2002). According to the multimedia effect or modality effect, the on-screen text with animation or with simulation is supposedly to be disadvantageous to their learning (Mayer, 1989, 2002; Mayer & Moreno, 1998, 2002; Mousavi et al., 1995). However, our results show that simulation participants performed statistically significantly better than animation participants when they received on-screen text. Hegarty (1992) reported that comprehension of the mechanics process is largely text directed and the diagram is inspected to check or to construct the representation of information read in the text. The design of Hegarty is quite close to our on-screen text with simulation except that ours is simulation instead of a diagram. The diagram is static allowing learners to control their learning pace when learning from a diagram with text, which is similar to the simulation with text. In addition, on-screen text has the advantage of being permanent and thus can be referred repeated (Kalyuga et al., 1999). However, animation would not be able to allow students to control their learning pace. It helps explain why simulation is better with animation when combined with on-screen text. Additionally, the animation with on-screen text would make students split their attention between on-screen text and pictorial areas and make their eyes move back and forth between on-screen text and pictorial areas without any control of the speed of animation. It might bring extra cognitive load on their working memory and impair their learning (Sweller & Chandler, 1994). Results demonstrated that the simulation with on-screen text group’s students allocated a greater number of fixations, longer inspection times, and a longer mean fixation duration on viewing both the pictorial area and the area of interest, which provide an evidence of the longer eye fixations the deeper information processing, thus result in better

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learning performance. It again supports the idea that eye-movement behavior is closely related to students’ deep cognitive processing of information and results in better learning performance (Rayner, 1998). Though the animation with narration participants allocated a greater amount of visual attention in the pictorial area and area of interest than the simulation with narration participants, however, the result of learning performance was not so obvious. According to the multimedia effect or modality effect, the narration with animation or narration with simulation is supposed to be advantageous to their learning (Mayer, 1989, 2002; Mayer & Moreno, 1998, 2002; Mousavi et al., 1995). Our results indicated that both groups performed about the same level on their post-test, and the animation-narration group performed only slightly better than the simulation-narration group on retention-test. Both instruction modes follow Mayer’s multimedia effect, which allows students to process information through both channels, therefore, the difference between the two groups in their immediate learning of mitosis and meiosis process was not so obvious (Mayer, 1989; Mayer & Moreno, 1998, 2002). Our findings demonstrated that the mean fixation duration and the total inspection time on viewing the pictorial area and area of interest were critical for the participants to acquire an understanding of the mitosis and meiosis processes. It supports previous studies which state that longer fixation durations are generally indicative of more extensive processing (Rayner, 1998). Specifically, the eye-movement data in the area of interest supports Underwood et al. (2008) study that longer inspection of the display, a greater number of fixations on the display, and longer durations of fixations are allocated to the areas of the scene that are judged as ‘‘informative”. Similar studies regarding eye movements have been recorded as participants solve math and physics problems, and these studies found that more complicated aspects of the problem typically lead to more and longer fixations (Hegarty & Just, 1993; Hegarty et al., 1992). Further studies support the idea that memory for a scene was related to the number of fixations made on the scene, and that more fixations yield higher recognition scores, which provides more support for our findings regarding the eye-movement pattern being consistent with students’ learning of science (Christianson et al., 1991; Loftus, 1972). The greater the eye fixation behavior, the deeper their cognitive processing is, therefore, those who had a longer viewing time, great fixation number, and longer fixation durations on both pictorial and area of interest were able to attain a better understanding of the mitosis and meiosis processes at a molecular level. 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