Influence of information presentation form on online learning based on dynamics theory of visual perception form

Abstract

With the development of information technology, online learning has become an important way of teaching in colleges and universities. The importance of online learning is particularly prominent, especially during the COVID-19 pandemic. How to improve online learning quality is a common problem faced by educators. Online learning quality is closely related to information presentation form, so it is necessary to study the influence of information presentation form on online learning. Based on the dynamics theory of visual perception form and its operating principle, this study compares the differences in post-test scores, cognitive load and satisfaction between the information dynamics presentation form and the traditional information presentation form through a two-factor random experiment. The data analysis shows that information presentation form plays a significant role in improving students’ academic performance and reducing cognitive load. To a certain extent, there search proves the effectiveness of the information presentation form based on dynamics theory of visual perception form in promoting online learning. Relevant improvement suggestions are proposed to provide a reference and basis for the in-depth development of online learning and the improvement of online learning quality.

Keywords

Dynamics theory of visual perception form information presentation form online learning associative cues CLC Number: G434 Document Code: A

1 Introduction

Since 2020, the education and teaching in domestic colleges and universities is adversely affected by the COVID-19 pandemic. To this end, the Ministry of Education issued the “Guiding Opinions on Doing a Good Job in the Online Teaching Organization and Management in General Institutes of Higher Learning during the Epidemic Prevention and Control”. It is proposed that universities should “suspend classes without suspending teaching and learning”, actively carry out online teaching activities such as online teaching and online learning, guarantee the teaching progress and teaching quality during the epidemic prevention and control period. Online teaching thus becomes an important part of college teaching. According to the Ministry of Education’s “National Undergraduate Education and Teaching Quality Report (2020)”, a total of 1.08 million teachers in undergraduate colleges and universities offered 1.1 million/17.19 million courses during the pandemic, a total of 3.5 billion college students attended online learning class, and the rate of online courses offered by colleges and universities nationwide reached 91%. How to improve online teaching quality has become an important issue faced by educational researchers [1]. Analysis on the research status of online learning at home and abroad reveals that the current research is mostly concentrated in system design and development, characteristics, influencing factors and effect evaluation, etc. Existing studies have confirmed significant impact of information presentation on learning. The information in the learning screen is not only a direct presentation of teaching information, but also instructs learners to pay attention to, select, organize and process information through presentation [2]. In information presentation research, previous researchers usually compared information presentation modes in multimedia, but failed to compare and evaluate information presentation forms. Ignoring the validity of information forms will have a negative impact on learning and downgrade learning effects [3]. How to present information content more effectively and improve teaching effect is an important issue of this research. Hence, based on the dynamics theory of visual perception form, this study investigates the influence of information presentation form on online learning.

2 An overview of the theory

2.1 The dynamics theory of visual perception form

Established on the basis of Gestalt psychology by Rudolf Arnheim, a world-renowned aesthetician and art psychologist, the dynamics theory of visual perception form is a set of aesthetic cognitive theory of the interaction between visual perception and psychological feelings in the field of art [4]. The theory takes “force” as the core concept, reveals the correlation between art form and visual perception, and interprets the physiological and psychological mechanisms of aesthetic experience [5].

Arnheim’s concept of visual perception is based on the pattern of force. According to him, under no circumstances does “stimulus” cause a static pattern. Through active organization in visual perception, the static properties of objects (such as shape, size, color) turn physical forms into visual dynamic forms, thus creating visual form structures that exist only in the observer’s experience or mental image [6]. Therefore, dynamic is the essence of perceptual experience, and visual perception exists in dynamic experience of visual perception form. That is to say, visual perception is not to passively accept, but is to create a formal structure suitable for the objective object, which is thus a cognitive behavior with general thinking [7].

2.2 The dynamics performance of visual perception form

The painter Ben Shahn said, “Form is the visual shape of content”. Arnheim believes that visual form is not a mechanical reproduction of physical shapes such as graphics and colors by visual perception, but is a product constructed by visual perception through a creative activity of interacting with physical shapes, which leads to an understanding of the nature of things. What particular combination of forms touches us? This involves the performance of dynamics. Arnheim defines “performance” from the following three aspects. First, the psychological counterpart of the dynamic process that leads to the production of perceptual stimuli [8]; second, organic or inorganic behaviors manifested in the dynamic appearance of perceptual object or event [9]; third, the ability of visual dynamics to state the dynamics of existence through the attributes of shape, color, and motion [10]. In other words, expressiveness is the visual perception form dynamics generated by the interaction between the appearance form stimulus of the visual object and the visual perception. Such expressiveness can only be presented through the visual perception form dynamics, which can be a conscious organism or an unconscious thing.

In the physical representation of dynamics, tilt, deformation and strobe flash are the three basic physical patterns that can present dynamics of visual perception form. Although the three basic physical patterns can stimulate dynamics of visual perception form, a picture’s existence can only be perceived when the dynamics of all its details comply with the comprehensive dynamics of its overall composition [9]. In terms of the physical style combination problem or composition problem of the visual perception form dynamics, Arnheim put forward a series of composition principles that can present the visual perception form dynamics in “The Power of the Center –Visual Art Composition Research”. Based on perceptual organization, these principles are composition principles of dynamics around the center, which are the basic compositional schema with universal validity [7].

In the psychological manifestation of dynamics, Arnheim believes that emotion is a universal perception and an interaction of perceptual power. The comparison between the expressiveness of things and the state of human psychology involves a secondary process. Expressiveness is the inherent nature of perceptual patterns, which occupies a priority position in human perceptual activities [6]. That is to say, if we want to scientifically understand something or state, we must first discover the pattern of its force, and illustrate its structural characteristics through the pattern of force [11]. Cognitive function is the creative activity of visual perception form dynamics. By abstracting the dynamic image of things through visual perception, it recognizes the essence of things. Such creative activity is reflected in the dynamics performance of visual perception form [7]. Take Fig. 1 as an example. When we look at Fig. 1 as a whole, the black circle is slightly off-center, which is the visual nature of Fig. 1. Instead of looking at the black circle or the square box in isolation, we immediately grasp the relationship between the two. At the same time, we also feel that the black circle not only leaves the center, but also displays a tendency to return to the center or further move away from the center, which gives people a sense of instability. It shows that when each thing appears, we immediately perceive its attributes and make visual judgments based on its attribute characteristics. The characteristic properties of perceptual objects have magnitude and direction, which are described as psychological “force”. The viewer’s intuitive feeling of perceptual objects is the visual thinking guided by visual experience, that is, the dynamics performance of visual perception mentioned above.

Fig. 1

The force in the graph.

2.3 The operation of visual perception form dynamics

The specific operation of visual perception form dynamics is based on Gestalt psychology’s “simplification principle”, “balance principle” and “inverse reduction principle”, all of which are reflected in the mental image created by visual perception and visual stimulation. The principle of simplification is a basic principle of Gestalt psychology, that “Any stimulus pattern tends tobe seen in such a way that resulting structure is as simple as the given conditions permits”. The principle of balance is that various factors in visual perception obtain a stable and in place configuration state under the action of visual perception dynamics, which can be physical balance or perceptual balance. Balance can eliminate the fuzziness and inconsistency of composition, which also increases the simplification of composition. The principle of inverse simplification is the interaction between the two struggles of human mental intuition to increase tension or reduce tension. Visual perception not only has a tendency to favor simplification and balance, but also has a tendency to increase tension by strengthening unbalance and deviating from simple pattern. Arnheim pointed out through a great number of psychological experiments that any thinking is carried out through images. Scholar Ning Hailin believes that the abstract activity of visual perception against visual stimuli constructs a mental image [7]. In other words, the visual perception form dynamics creates an image, and an image is a gestalt including objects, behaviors, concepts and other forms [7]. Therefore, image is the bond between vision and thinking, also the pattern of visual perception form dynamics.

The generation of image is an abstract selection of visual perception “from the whole to the part”, the processing activity of “complement” and “reconstruction” of visual objects, and the germinal activity construction based on “intention” of the two [7]. “Complement” means, through perceptual organization activities, invisible part will be included into the real part of the object, rather than limited to the material directly presented in front of us. “Reconstruction” means that visual perception can reorganize physical properties such as color and shape to make it conform to a certain order structure. The construction of germinal activities of “intention” relates to Arnheim’s discussion on “Dynamics Concept” and “Standard Image”. The overall working process of visual perception form dynamics is shown in Fig. 2.

Fig. 2

The dynamics operation process of visual perception form.

2.4 Research on the influence of information presentation form on online learning

A large number of empirical studies have shown that information presentation form affects online learning. For example, Eitel et al. believed that, compared with mere text, presenting images first and then text can help us gain understanding [12]. Mayer et al. pointed out that, by presenting images and texts at the same time, subjects can create more problem-solving creative solutions than in successive presentations [13], which also facilitates students’ use of knowledge [14], and enables better understanding and transfer of knowledge [15]. Wen believes that if the deep logical relationship between pictures and texts is not effectively linked, emphasizing pictures over text, and splitting pictures and texts in design will sabotage the organic integration between pictures, texts and long-term memory in the working memory stage, thus affecting the improvement of learning effects [2]. Ayres and Sweller pointed out that the synchronization of images and text in time and the adjacent arrangement in space can improve academic performance [16]. Wang and Dong conducted a comparative study on the design principles of foreign teaching videos, and pointed out in the conclusion that by changing the font color, size to emphasize information change and using the guidance animation to prompt the teaching content, it is possible to improve the teaching video quality [17]. Zip roved through experiments that the use of virtual reality information presentation forms can visualize abstract knowledge, promote knowledge understanding, improve academic performance, increase student attention and satisfaction [18].

To conclude, there are different research directions and viewpoints on the influence of information presentation forms on online learning, and a relatively unified conclusion has not yet been formed, so its influence mechanism demands further clarification. Visual perceptual form dynamics is an important factor affecting learners’ thinking, and current research has rarely explored in depth from this perspective. The purpose of information design in online learning is to promote learning, but many teachers still have not fully realized the influence degree of information presentation form on online learning when preparing multimedia teaching materials. Hence, there is need to further improve the scientific and rational understanding, support design with theory. Therefore, based on the dynamics theory of visual perception form, this study investigates the influence of information presentation form designed according to its operating principles and composition principles on online learning. It attempts to optimize the task process of learners’ visual thinking and help learners form a coherent mental representation via the learning information.

3 Research design

3.1 Experimental subjects

The study is to explore the differences in post-test scores, cognitive load and satisfaction of learners after online learning in the form of information dynamic presentation and traditional information presentation. In this experiment, full-time students from some colleges and universities in City C were randomly selected as subjects, and their majors were not limited. There were total number of 100 participants in the experiment, including 73 girls and 27 boys. All subjects had normal vision or corrected vision, no color blindness or color weakness, who were randomly assigned to four groups, namely “traditional presentation without cues” (25 subjects), “traditional presentation with cues” (25 subjects), “dynamic presentation without cues” (25 subjects), and “dynamic presentation with cues” (25 subjects).

3.2 Experimental design

The experiment adopts a two-factor completely randomized experimental design with 2 information presentation forms (traditional information presentation, information dynamics presentation)×2 associative cues (with and without). The independent variables in this experiment are information presentation form and associative cues, and the dependent variables include post-test scores, cognitive load, and satisfaction. The control variable is prior knowledge level. The details of the information dynamics design are shown in Table 1.

Table 1
Information dynamic design details

Experimental factor Principles Dynamic performance emphasis Goal

Information presentation form Simplification, balance, and inverse simplification principles Physical performance Stimulate dynamic creative activities

Associative cue Simplification, balance principles Mental performance Stimulate dynamic creative activities

Experimental factor	Principles	Dynamic performance emphasis	Goal
Information presentation form	Simplification, balance, and inverse simplification principles	Physical performance	Stimulate dynamic creative activities
Associative cue	Simplification, balance principles	Mental performance	Stimulate dynamic creative activities

3.3 Experimental tools

3.3.1 Learning materials

The experimental material of this research is “Space Application in Posters” in the poster design course. The materials were compiled with reference to poster design books, and four sets of video materials with the same teaching content were designed and produced, namely “traditional presentation without cues”, “traditional presentation with cues”, “dynamic presentation without cues”, “dynamic presentation with cues”. The four sets of video materials have a production time of about 8 minutes and 00 seconds (the time difference between the four sets of videos is less than 5 seconds), with the same voiceover (male voice), same resolution (1080P), same format (.MP4).

3.3.2 Subject materials

Prior knowledge questionnaire. The prior knowledge questionnaire was designed to measure the subject’s understanding of poster design knowledge before online learning, so that differences in subjects’ prior knowledge would not affect the experimental results. The prior knowledge questionnaire was designed and modified with reference to the existing research literature. The Cronbach’s Alpha value in the questionnaire was 0.926, which had high reliability. Cronbach’s Alpha is a statistic, which refers to the average of the half-reliability coefficient obtained from all possible item division methods of the scale, and is the most commonly used reliability measurement method. The Cronbach α coefficient is usually between 0 and 1. If the α coefficient does not exceed 0.6, the internal reliability is generally considered to be insufficient. 0.7–0.8 indicates that the scale has considerable reliability, and 0.8–0.9 indicates that the scale has very good reliability. The questionnaire was evaluated using the Likert five-point scoring method. The range of poster knowledge points was arranged from large to small to ensure the measurement accuracy.

Post-test score test. The post-test paper was designed to measure students’ understanding and memory of the knowledge points about “spatial use in posters” in the four experimental groups after learning through video materials. The test consists of 10 true or false questions, each with 10 points, totaling 100 points. A higher score indicates better learning effect. All test questions were prepared by professional visual communication design teachers according to the learning materials to guarantee validity.

Cognitive load measurement scale. The cognitive load measurement scale in this experiment is the NASA-TLX (NASA Task Load Index) evaluation scale proposed by Hart and Stave land in 1988. This scale is considered as the most widely used and most accepted subjective assessment tool of mental load [19].

Online learning satisfaction questionnaire. The online learning satisfaction questionnaire in this experiment was designed and modified based on the student satisfaction questionnaire of Yu-Chun Kuo et al. and Zhang Rui’s learning satisfaction questionnaire, which was then reviewed and finalized by experts. In the questionnaire, Cronbach’s Alpha value = 0.871, indicating that the questionnaire has high reliability.

4 Data analysis

In this study, the relevant data of the students in the four experimental groups were tested for significance in the prior knowledge questionnaire, and the results were: F(3,100) = 0.740, P > 0.05.The results indicate that the students in the four experimental groups have no significant difference in prior knowledge level, so there is no effect on the post-test results of the experiment. Therefore, this experiment supports subsequent measurement and analysis. Abbreviated interpretation: ANOVA –analysis of variance, F –ratio of the mean square between groups to the mean square within groups, P –probability of significance, M –mean, SD –standard deviation, η² –effect size of analysis of variance.

The experimental data are shown in Table 2 (due to the large number of data, only 30 samples are shown as representatives).

Table 2
Part of the experimental data

No. Information presentation form Associative cue Score Total load Satisfaction

1 Dynamic presentation With cue 80 10.2 20

2 Dynamic presentation With cue 60 9.533333333 20

3 Traditional presentation Without cue 20 16.4 22

4 Traditional presentation Without cue 50 10.93333333 20

5 Dynamic presentation With cue 80 8.733333333 17

6 Traditional presentation Without cue 40 15.93333333 25

7 Dynamic presentation Without cue 60 14.93333333 25

8 Dynamic presentation With cue 50 14.33333333 21

9 Traditional presentation With cue 30 10.26666667 20

10 Dynamic presentation With cue 90 5 20

11 Dynamic presentation With cue 80 11.06666667 19

12 Traditional presentation With cue 80 7.266666667 19

13 Dynamic presentation Without cue 70 9.866666667 25

14 Dynamic presentation Without cue 20 9.533333333 22

15 Dynamic presentation Without cue 60 12 20

16 Dynamic presentation Without cue 70 13.6 15

17 Dynamic presentation Without cue 70 11 25

18 Dynamic presentation Without cue 100 7.8 15

19 Traditional presentation Without cue 20 14.13333333 25

20 Traditional presentation With cue 70 14.93333333 20

21 Dynamic presentation With cue 90 9.8 25

22 Traditional presentation With cue 60 15.86666667 25

23 Traditional presentation With cue 100 14.73333333 23

24 Traditional presentation With cue 100 12.6 18

25 Traditional presentation With cue 80 12.13333333 20

26 Traditional presentation With cue 100 16.53333333 18

27 Traditional presentation With cue 50 12.66666667 25

28 Traditional presentation Without cue 60 12.2 22

29 Dynamic presentation With cue 60 10.86666667 15

30 Traditional presentation With cue 90 11.4 22

No.	Information presentation form	Associative cue	Score	Total load	Satisfaction
1	Dynamic presentation	With cue	80	10.2	20
2	Dynamic presentation	With cue	60	9.533333333	20
3	Traditional presentation	Without cue	20	16.4	22
4	Traditional presentation	Without cue	50	10.93333333	20
5	Dynamic presentation	With cue	80	8.733333333	17
6	Traditional presentation	Without cue	40	15.93333333	25
7	Dynamic presentation	Without cue	60	14.93333333	25
8	Dynamic presentation	With cue	50	14.33333333	21
9	Traditional presentation	With cue	30	10.26666667	20
10	Dynamic presentation	With cue	90	5	20
11	Dynamic presentation	With cue	80	11.06666667	19
12	Traditional presentation	With cue	80	7.266666667	19
13	Dynamic presentation	Without cue	70	9.866666667	25
14	Dynamic presentation	Without cue	20	9.533333333	22
15	Dynamic presentation	Without cue	60	12	20
16	Dynamic presentation	Without cue	70	13.6	15
17	Dynamic presentation	Without cue	70	11	25
18	Dynamic presentation	Without cue	100	7.8	15
19	Traditional presentation	Without cue	20	14.13333333	25
20	Traditional presentation	With cue	70	14.93333333	20
21	Dynamic presentation	With cue	90	9.8	25
22	Traditional presentation	With cue	60	15.86666667	25
23	Traditional presentation	With cue	100	14.73333333	23
24	Traditional presentation	With cue	100	12.6	18
25	Traditional presentation	With cue	80	12.13333333	20
26	Traditional presentation	With cue	100	16.53333333	18
27	Traditional presentation	With cue	50	12.66666667	25
28	Traditional presentation	Without cue	60	12.2	22
29	Dynamic presentation	With cue	60	10.86666667	15
30	Traditional presentation	With cue	90	11.4	22

4.1 Differences in the influence of information presentation forms and associative cues on online learning performance

In order to examine the influence of information presentation forms andassociative cues on online learning, in this study, the students’ answer sheets in the four experimental groups were scored in the post-test, and SPSS 22.0 was used to conduct two-way ANOVA of two information presentation forms (traditional information presentation, dynamic information presentation)×2 associative cues (with and without).The analysis steps are as follows: Select “Analysis” ⟶ “General Linear Model” ⟶ “Univariate” in the SPSS menu, and then, select the example data table Then, select “Achievement” as the dependent variable, “Information presentation form” and “Associated cues” as independent variables in the example data table to conduct a two-factor ANOVA, specify “Model “Model” as the full factor, select “Descriptive statistics”, “Homogeneity test” and “Efficacy After “Estimation”, click “OK” to generate the SPSS two-factor ANOVA results. The descriptive statistics include the mean, standard deviation and frequency (N) of the data for each group of experiments. The homogeneity test compares whether the distribution of the two groups of data is the same and can be compared in the next step, and the original hypothesis can be accepted if the p-value is > 0.05. The test P value of the ANOVA test represents the main effect difference significance, and the probability of significance P value < 0.01 indicates a strong judgment result, 0.01 < P value < 0.05 indicates a weaker judgment result, and P value > 0.05 indicates no judgment result. The power estimate is an ANOVA effect size indicator, and η² indicates the magnitude of the overall variance variation in the dependent variable that can be explained by this independent variable. The specific results are shown in Tables 3 , and 5.

Table 3
Descriptive statistics of post-test scores of the four experimental groups

Information presentation form Associative cue Average score Standard deviation N

Traditional presentation without cue 43.60 19.122 25

Traditional presentation with cue 72.80 19.261 25

Dynamic presentation without cue 71.60 19.723 25

Dynamic presentation with cue 78.00 14.142 25

Information presentation form	Associative cue	Average score	Standard deviation	N
Traditional presentation	without cue	43.60	19.122	25
Traditional presentation with cue		72.80	19.261	25
Dynamic presentation without cue		71.60	19.723	25
Dynamic presentation with cue		78.00	14.142	25

Table 4

Homogeneity of variance test for posttest scores

Levene statistics	Degrees of freedom 1	Degrees of freedom 2	Significance
.943	3	96	.423

Table 5

Inter-subject effect test of post-test scores

Source	F	Significance	Local Eta Square
Information presentation form	20.787	.000	.178
Associative cue	23.900	.000	.199
Information presentation form* Associative cue	9.803	.002	.093

The experimental results of the post-test score show that, the homogeneity of variance test for posttest scores p-value = 0.423 > 0.05, the variance is flush and can be further tested. The main effect of the information presentation form is significant F(1,100) = 20.787, P = 0.000 < 0.01, η² = 0.178.The dynamic presentation group in the information presentation form (M = 71.60, SD = 19.723; M = 78.00, SD = 14.142) has higher average score than the traditional presentation group (M = 43.60, SD = 19.122; M = 72.80, SD = 19.261). The main effect of associative cues is significant F(1, 100) = 23.900, P = 0.000 < 0.01, η² = 0.199.The group with associative cue (M = 72.80, SD = 19.261; M = 78.00, SD = 14.142) has higher average score than the group without cue (M = 43.60, SD = 19.122; M = 71.60, SD = 19.723). The interaction between information presentation form and associative cues is significant F(1, 100) = 9.803, P = 0.002 < 0.01, η² = 0.093.

4.2 Differences in the influence of information presentation forms and associative cues on cognitive load of online learning

In this study, two-way ANOVA was performed on the relevant data in the cognitive load measurement scale of the students in the four experimental groups. The results are shown in Tables 6, 7 and 8 , Tables 6, 7 and 8.

Table 6
Descriptive statistics of cognitive load in the four experimental groups

Information presentation form Associative cue Average score Standard deviation N

Traditional presentation Without cue 13.50 1.856 25

Traditional presentation with cue 12.15 3.571 25

Dynamic presentation without cue 10.78 2.377 25

Dynamic presentation with cue 9.18 2.521 25

Information presentation form	Associative cue	Average score	Standard deviation	N
Traditional presentation	Without cue	13.50	1.856	25
Traditional presentation with cue		12.15	3.571	25
Dynamic presentation without cue		10.78	2.377	25
Dynamic presentation with cue		9.18	2.521	25

Table 7

Homogeneity of cognitive load variance test

Levene statistics	Degrees of freedom 1	Degrees of freedom 2	Significance
2.178	3	96	.096

Table 8

Inter-subject effect test of cognitive load

Source	F	Significance	Local Eta Square
Information presentation form	28.737	.000	.230
Associative cue	7.670	.007	.074
Information presentation form * Associative cue	.055	.816	.001

The cognitive load experimental results show that, the homogeneity of variance test for posttest scores p-value = 0.096 > 0.05, the variance is flush and can be further tested. The main effect of the information presentation form is significant F(1,100) = 28.737, P = 0.000 < 0.01, η² = 0.230.The dynamic presentation group in the information presentation form (M = 10.78, SD = 2.377; M = 9.18, SD = 2.521) has lower cognitive load than the traditional presentation group (M = 13.50, SD = 1.856; M = 12.15, SD = 3.571). The main effect of associative cues is significant F(1, 100) = 7.670, P = 0.007 < 0.01, η² = 0.074. The group with associative cue (M = 12.15, SD = 3.571; M = 9.18, SD = 2.521) has lowercognitive load than the group without cue (M = 13.50, SD = 1.856; M = 10.78, SD = 2.377). However, the interaction between information presentation form and associative cues is not significant F(1,100) = 0.055, P = 0.816 > 0.05, η² = 0.001.

4.3 Differences in the influence of information presentation forms and associative cues on online learning satisfaction

In this study, two-way ANOVA was performed on students’ relevant data in the online learning satisfaction scale of the four experimental groups, with the results shown in Tables 9 , 10 and 11.

Table 9
Descriptive statistics of online learning satisfaction in the four experimental groups

Information presentation form Associative cue Average score Standard deviation N

Traditional presentation Without cue 19.80 3.240 25

Traditional presentation With cue 22.04 3.323 25

Dynamic presentation Without cue 20.84 3.520 25

Dynamic presentation With cue 21.92 2.629 25

Information presentation form	Associative cue	Average score	Standard deviation	N
Traditional presentation	Without cue	19.80	3.240	25
Traditional presentation	With cue	22.04	3.323	25
Dynamic presentation	Without cue	20.84	3.520	25
Dynamic presentation	With cue	21.92	2.629	25

Table 10

Homogeneity of variance test for online learning satisfaction

Levene statistics	Degrees of freedom 1	Degrees of freedom 2	Significance
.477	3	96	.699

Table 11

Inter-subject effect test of online learning satisfaction

Source	F	Significance	Local Eta Square
Information presentation form	0.518	.473	.005
Associative cue	6.747	.011	.066
Information presentation form * Associative cue	0.824	.366	.009

The experimental results of the online learning satisfaction show that, the homogeneity of variance test for posttest scores p-value = 0.699 > 0.05, the variance is flush and can be further tested. The main effect of the information presentation form is not significant, F(1,100) = 0.518, P = 0.473 > 0.05, η² = 0.005. However, the edge effect of associative cues is significant F(1, 100) = 6.747, P = 0.011 < 0.05, η² = 0.066. The group with associative cue (M = 22.04, SD = 3.323; M = 21.92, SD = 2.629) has higher online learning satisfaction than the group without cue (M = 19.80, SD = 3.240; M = 20.84, SD = 3.520). The interaction between information presentation form and associative cues is not significant F(1,100) = 0.824, P = 0.366 > 0.05, η² = 0.009.

5 Experimental results and analysis

5.1 Experimental results

This study analyzes the influence of information presentation form on online learning. By comparing the four sets of experimental data, the following conclusions can be drawn.

5.1.1 The influence of information presentation form on online learning

In information presentation form, the dynamic presentation group had significantly higher post-test scores, lower cognitive load than the traditional presentation group, and there was no significant difference in online learning satisfaction between the dynamic presentation group and the traditional presentation group.

5.1.2 The influence of associative cues on online learning

The group with associative cue had significantly higher post-test scores, lower cognitive load and higher online learning satisfaction than the group without cue.

5.1.3 The influence of the simplicity effect on online learning

Information presentation forms and associative cues have significant interactive effects on post-test scores. Under dynamic information presentation form, the group with associative cue had higher post-test scores than the group without cue. Under traditional information presentation form, the group with associative cue had higher post-test scores than the group without cue. Information presentation forms and associative cues had no interactive effects on cognitive load and online learning satisfaction.

5.2 Analysis on the influence of information presentation form on online learning

5.2.1 The dynamic design of information presentation forms plays a significant role in improving online learning performance and lowering cognitive load

Arnheim believes that visual perception requires understanding, and its cognitive activities are active exploration, selection, simplification, abstraction, analysis, solution of information. Visual perception is selective, and active selection avoids energy waste, which also makes its response faster and more robust by confining perception to only a limited number of options [11]. The experiments by Pollock et al. also show that learning by breaking down knowledge modules and presenting them one by one yields significantly higher learner’s performance compared to learning via the whole block of knowledge and simultaneous presentation. It is because the way of breaking down the modules can let the learner first complete knowledge construction for some modules. Afterwards, even if all learning materials are presented, learners have formed schemas in long-term memory through the previous knowledge construction, thereby reducing the working memory burden and lowering cognitive load [20].

In this experiment, in terms of information presentation form, the entire text was classified according to the main points and divided according to importance based on the principle of simplification and balance in dynamics operation. Then, according to the basic composition principle of dynamics, spatial distinction and visual attention were strengthened via style attributes of color, direction, size, shape, etc. to improve the information organization, optimize the visual thinking task of the subjects, and effectively distribute the subject attention, so that subjects discover, identify and memorize knowledge points faster. It thus reduces the number of chunks in working memory, increases the information contained in the unit chunks and enhances the learning effect.

5.2.2 The establishment of associative cues plays a significant role in improving online learning performance, reducing cognitive load, and increasing satisfaction

According to the knowledge construction hypothesis, cues can serve as a cognitive guide to help learners understand the presented material [21]. Meyer defines textual cues as an approach of not conveying content information in an article, but providing guidance to readers by emphasizing certain semantic content, or pointing out certain content structure, so that readers can more clearly see what relationship is stated in the article [22]. Thus, Mautone and Mayer argue that, to some extent, textual cues seem to function by instructing learners to select, organize, and integrate interpretive information [21]. Learners are disturbed by the complexity of learning materials when learning materials. Pollock et al. believe that in order to promote learning and understanding, the inherent cognitive load of the material should be artificially reduced [20]. By eliminating interactions between information elements, creating “isolated elements”, we can handle working memory sequentially rather than processing information elements simultaneously, thereby reducing working memory load [20]. The “isolated element” mentioned here is the key information under the guidance of associative cues. As a salient stimulus, associative cue can instruct learners to pay attention to important information, reduce the processing of irrelevant information, establish a coherent information structure or emphasize organizational relationship in information, thereby connecting new knowledge with original knowledge [23].

In this experiment, the cues include non-content information such as colors, arrows, graphics, and words. According to the simplification principle of dynamics operation, the abstract activities of visual perception allow faster image construction by designing inclination, deformation and other styles, so that subjects understand things and stimulate psychological feelings. In other words, associative cues will instruct the subjects to pay attention to key information, shorten the information search time, and at the same time establish the connection between images and words, thus helping the subjects construct a coherent mental representation, integrate knowledge information, which enhances learner satisfaction and ultimately increases learning outcomes.

5.3 The coordination and unification of information presentation form and associative cue design help improve online learning performance

Arnheim believes that “relationship depends on structure”, any “seeing” is viewing from a set of relations, and the relational network in which the perceptual object is located is by no means simple. For anything that appears in the field of view, its pattern or appearance is determined by its position and function in the overall structure, and the thing itself will undergo fundamental changes under the influence of this overall structure. This also explains why the design of information presentation form brings a significant effect. Through the designed information presentation form, in the process of “learning”, the most unique aspect (or feature) of the “learned” object quickly assumes a prominent position. Its difference (or uniqueness) from other things lies in either “kind” or “degree”. For example, the “spatial direction” knowledge point forms a whole paragraph of text in the undersigned material, and it is difficult to quickly sort the relationship between the knowledge points, while design based on the similarity rule solves the above problem. At the same time, Arnheim also emphasized that perception takes time, and perception is not a simple, direct and purely perceptual reflection activity, but an intertwined, selective, abstract, and even creative construction activity. This activity requires changes of different stages and different natures, in which, these stages and natures are derived from each other, but each remains independent, thus maintaining an organized state within its own scope. Only after these changes can the predetermined goal be accomplished [11]. Associative cues have the functions of attention guidance, information organization, and information integration in multimedia information integration. Generally, changing stimuli such as colors, graphics, and arrows are used as cues, which belong to salient stimuli [23, 24]. According to perceptual processing theory, stimuli or targets with discriminative features facilitate visual search [25, 26], because salient stimuli can automatically capture attention and affect the subjects’ perceptual choices when processing information, thereby shortening information search time and releasing more cognitive resources for information integration and material organization [27, 28].

In this experiment, associative cues of non-content information facilitate the subjects’ attention and understanding of the information presentation form. Reasonable design of information presentation form coupled with associative cues can play a role in improving the learning effect.

6 Research implications

Experiments have confirmed the influence of rational design of information presentation form and associated cues on the optimization of learning performance and cognitive load. Based on the above conclusions, the following suggestions and innovative design schemes are proposed in this study:

6.1 Improve teachers’ visual literacy and design literacy, and carry out special training on teachers’ information technology application ability

High-quality instructional information design should meet the needs of learners by giving comprehensive considerations to design theory, design technology, discipline characteristics and learner characteristics. The survey found that, in the process of teaching information design, teachers tend to design teaching resources with teachers as the center, ignoring the learning needs of learners; some teachers lack theoretical basis guidance in design principles, and their messy and complicated teaching design information hinders learners’ cognition. Young teachers believe that the difficulty of teaching information design lies in time and efficiency, while middle-aged and elderly teachers believe that function and design methods are the main obstacles [29 –31]. Therefore, in response to the Ministry of Education’s requirements of “actively carrying out online teaching activities such as online teaching and online learning to guarantee the teaching progress and teaching quality during the epidemic prevention and control period”, relevant teaching units should give training courses on teachers’ information technology application ability. Training courses should be divided in terms of content and levels according to needs, and relevant knowledge such as dynamics theory of visual perception form, design skills, and network platforms should be incorporated to meet diversity requirements for teachers.

6.2 Reasonably divide the teaching content into chunks, and guarantee the coherence and integrity of the teaching content

According to Pollock’s point of view in the above analysis, the interaction between information elements can be eliminated to artificially reduce the inherent cognitive load of the material, so that learners can avoid processing all information elements at the same time and reduce the load of working memory. We can divide the teaching content into chunks according to the simplification and balance principles of the dynamics theory of visual perception form. By only presenting one or a few knowledge points in each teaching video or picture unit, it is possible to avoid simultaneous information processing by learners and reduce the learning difficulty. However, it is necessary to ensure the integrity of the teaching content to some extent so that learners can establish a clear and complete knowledge system. Short instructional videos and targeted learning goals are also very important [32].

6.3 Visual design of the screen should be carried out according to the cognitive laws by focusing on the visual psychological characteristics of learners

Arnheim pointed out that the relationship between the various components in the perceptual field will not be as simple as the relationship model proposed by traditional association theory, but will form a strong relationship bond when the background structure is strengthened or supported. This relationship constrains each component [11]. Therefore, in instructional design, information presentation form can be used to inform learners about the relationship and function value of the teaching content, organize related elements together according to the basic composition principle of visual perception form dynamics, thus highlighting the category of teaching content via distance and density. The associative cues of interactive elements can be used to guide learners’ visual attention, quickly grasp the teaching focus, and clarify the hierarchical relationship. In the use of associative cues, we should pay attention to meet the needs of learners with different cultural backgrounds, create conditions for them to connect new and old knowledge, and improve the learning effect by enabling meaningful learning [33].The collocation of elements such as colors, lines, and graphics should conform to the principles of aesthetic design, and rational use will add visual effect to the picture. We should keep the picture design simple in unified style, avoid excessive color accumulation and element collocation. Generally, there should be no more than 3 auxiliary elements and colors in the same picture, and the picture style of the same group of knowledge points should be consistent.

6.4 Pay attention to quality control of audio-visual media and enhance the complementarity of elements

Online learning is mostly to simultaneously present visual elements and audio to convey and explain the teaching content, so it is necessary to consider how to make these elements complement each other without redundancy. On the basis of reasonable information presentation form, we should also pay attention to picture clarity in visual elements, try to use resolution materials of the same quality or use vector materials in design when technical ability permits, so as to avoid adding extra cognitive load to the learners. The changes in the guiding cues of the picture (such as flashing, highlighting, transformation, etc.) should be synchronized with the auditory channel. If the teacher cannot control the media effect well, the dynamic change can be cancelled to avoid distracting learners.

6.5 Master the characteristics of individual differences through interactive feedback between teachers and students, and design innovative teaching programs centered on learners

The individual difference of learners is the key factor that affects the learning effect. In order to meet the learning needs of different learners, teachers should understand the characteristics of each learner so as to obtain a better teaching plan. The innovation of such a scheme should be carried out both technically and psychologically. In terms of technology, teachers need to add some favorite or popular topics, interactions or media of learners, such as online communication platform, H5, AR, VR, etc., to constantly update and innovate teaching design schemes through real-time feedback; Psychologically, the innovative design of teaching should also be carried out in a learner-centered way, which can be leap-forward, story-guided, enlightening or practical, instead of teaching in the usual sequence that teachers are accustomed to. The innovative teaching plan should be supported by the content suggested above and carried out under the premise of reasonable control of teaching content, teaching picture and media quality [34].

7 Research conclusions

This study analyzed the influence of the form of information presentation on online learning based on the formal dynamics theory of visual perception. With the maturity of information technology and the rapid development of Internet education, online learning has become an important way of teaching in colleges and universities. The outbreak of COVID-19 makes online learning especially important. However, visual perception is considered as an aspect of online learning research, and it is considered as an understudied problem. Through the combination of theoretical research and practical teaching research, this study designed a two-factor randomized experiment to verify the improvement of students’ learning motivation and learning effect in the form of information dynamic presentation in teaching. It can be seen from the experimental data that the performance of learners in teaching with information dynamic presentation is significantly higher than that of traditional information presentation, and the cognitive load is lower than that of traditional information presentation. This is because the information dynamic presentation effectively guides learners’ attention and promotes learners’ understanding. The addition of associative cues in teaching can enhance the coherence of information exploration, reduce the load of working memory, and help learners construct mental representations faster in connecting old and new knowledge. Smooth understanding will promote learners’ satisfaction and interest in learning. Therefore, this study verified the feasibility of the formal-dynamic theory of visual perception to help improve the instructional design and improve the effect of online learning. Educators should consider learners’ visual thinking and carry out teaching design according to the theory of visual perception formal dynamics, so as to improve learners’ learning quality and effect.

However, this study also has some limitations, such as the information presentation form only focuses on the relationship effectiveness of the combination of text and text, and the knowledge category is relatively single. Subsequent research will increase the depth and breadth of the experiment and carry out research on different presentation forms of learning materials, such as dynamic charts, short videos, AR technology and other material media. At the same time, the research objects are not only limited to colleges and universities, but also involved in the online teaching of primary and secondary schools, and strive to provide more favorable theoretical and practical basis for the in-depth development of online learning.

Declarations

Data availability statement

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Conflicts of interest

It is declared by the authors that this article is free of conflict of interest.

Funding statement

No funding was received.

Footnotes

Acknowledgments

Not applicable.

Authors’ contributions

The author completed this manuscript independently.

References

Zhao

, Quality management of online teaching in colleges and universities in the post-epidemic era, Modern Education Management (05) (2021), 107–112.

Wen

X.Y.

, Research on the construction of design rules for the integration of educational graphics and text, Tianjin Normal University, 2017.

and Yang

X.M.

, Research on the construction of design rules for the integration of educational graphics and text, Tianjin Normal University, 2017.

M.C.

, Aesthetic research on non-European architectural forms based on the dynamics theory of visual perception, Southeast University, 2016.

L.F.

, Arnheim’s dynamics theory of visual perception form and dynamic cartoon creation, Journal of Anhui Normal University (Humanities and Social Sciences Edition) 44(05) (2016), 640–645.

Arnheim

, Art and Visual Perception (50th Anniversary Edition), Sichuan People’s Publishing House, 2019.

Ning

H.L.

, Research on Arnheim’s dynamics theory of visual perception form, People’s Publishing House, 2009.

Arnheim

, Towards the Psychology of Art, Yellow River Literature and Art Publishing House, 1990.

Arnheim

, Art and Visual Perception, University of California Press, 1974.

10.

Arnheim

, The Power of the Center: A Study of Composition in the Visual Arts: The New Version, University of California Press, 1988.

11.

Arnheim

, Visual Thinking: The Psychology of Aesthetic Intuition, Sichuan People’s Publishing House, 2010.

12.

Eitel

, Scheiter

and Schüler

, How inspecting a picture affects processing of text in multimedia learning, Applied Cognitive Psychology 27(4) (2013), 451–461.

13.

Mayer

R.E.

, Steinhoff

, Bower

, et al., A generative theory of textbook design: Using annotated illustrations to foster meaningful learning of science text, Educational Technology Research and Development 43(1) (1995), 31–41.

14.

Mayer

R.E.

, Heiser

and Lonn

, Cognitive constraints on multimedia learning: When presenting more material results in less, Journal of Educational Psychology 93 (2001), 187–198.

15.

Carlson

, Chandler

and Sweller

, Learning and understanding science instructional material, Journal of Educational Psychology 95(3) (2003), 629–640.

16.

Ayres

and Sweller

, The split-attention principle in multimedia learning, The Cambridge Handbook of Multimedia Learning 2 (2005), 135–146.

17.

Wang

and Dong

L.L.

, An international comparative study on the principles of MOOC instructional video design, The Chinese Journal of ICT in Education (22) (2018), 10–15.

18.

, Research on the effect of virtual reality-based information presentation form on the learning effect of high school students, Tianjin Foreign Studies University, 2022.

19.

Yang

and Deng

C.P.

, Research on the reliability and validity of NASA-TLX Scale as a subjective fatigue assessment tool for computer work, Psychological Research (30) (2010), 36–41.

20.

Pollock

, Chandler

, Sweller

, et al., Assimilating complex information, Learning and Instruction 12(1) (2002), 61–86.

21.

Mautone

P.D.

and Mayer

R.E.

, Signaling as a Cognitive Guide in Multimedia Learning, Journal of Educational Psychology 93(2) (2001), 377–389.

22.

Meyer

B.J.F.

, The organization of prose and its effects on memory, Amsterdam; Oxford: North-Holland Publishing Company, 1975.

23.

Wang

F.X.

, Duan

Z.H.

and Zhou

Z.K.

, The role of cues in multimedia learning, Advances in Psychological Science 21(08) (2013), 1430–1440.

24.

Zheng

and Yin

, Characterization inference based on joint-optimization of multi-layer semantics and deep fusion matching network, PeerJ Computer Science, 2022.

25.

Itti

and Koch

, A saliency-based search mechanism for overt and covert shifts of visual attention, Vision Research 40(10-12) (2000), 1489–1506.

26.

Zhou

, Lv

, Lei

, et al., Global and local-contrast guides content-aware fusion for RGB-D saliency prediction, IEEE Transactions on Systems Man Cybernetics-Systems 51 (2021), 3641–3649.

27.

Mayer

R.E.

, Cognitive theory of multimedia learning, The Cambridge Handbook of Multimedia Learning 41 (2005), 31–48.

28.

, Zheng

, Xia

, et al., Data quality matters: a case study on data label correctness for security bug report prediction, IEEE Transactions on Software Engineering, 2021, 1.

29.

Tang

S.R.

, Leng

, Tan

J.B.

, et al., Research on effective strategy for teaching PPT design, The Chinese Journal of ICT in Education (02) (2021), 78–82.

30.

Chen

, Du

and Guo

, Label constrained convolutional factor analysis for classification with limited training samples, Information Sciences 544 (2021), 372–394.

31.

Chen

G.M.

, Chen

P.R.

, Huang

W.X.

, et al., Continuance intention mechanism of middle school student users on online learning platform based on qualitative comparative analysis method, Mathematical Problems in Engineering 2022 (2022), 12.

32.

Brame

C.J.

, Effective educational videos: Principles and guidelines for maximizing student learning from video content, CBE-Life Sciences Education 15(4) (2016), es6.

33.

Wang

, Zhou

, Wang

Z.J.

, et al., Research on the optimization design of MOOC teaching video-a case study of top 20 MOOC from the American curriculum central website, Distance Education in China (5) (2018), 45–54.

34.

Huang

, Han

, Li

, et al., Sentiment evolution with interaction levels in blended learning environments: Using learning analytics and epistemic network analysis, Australasian Journal of Educational Technology 37(2) (2021), 81–95.