Digital Technology-Driven Transformation of Teaching Model in Animation Film Program and Enhancement of Students’ Artistic Literacy

In the age of information technology, images have become an important aesthetic way for people. Animated film is an important component structure in film art, animated film teaching should be combined with the contemporary audience’s aesthetic needs and cultural connotation needs, actively explore a more practical and innovative teaching methods, deeply excavate the aesthetic and cultural significance of animated film, improve the depth of thought in professional teaching, and guide professionals to control the viewing psychology of animated film audience [1-4].

The teaching purpose of the animated film course is to let students master the whole process of film and television production, that is, from the comprehensive preparation to the mid-term practice of filming, and then to the post-production of the three steps, can be the course of film and television production theory skillfully applied to the practical operation, and be able to independently produce film and television scripts, screenplay scripts, filming and editing, and thus learn to analyze the creative process, shooting and editing of film and television clips [5-7]. Animation film courses in colleges and universities are aimed at cultivating outstanding talents with profound film and television literacy, solid film and television knowledge and practical innovation ability, and laying a solid film and television foundation for the students’ personal growth and development, professional course learning and future employment, as well as implementing the fundamental task of promoting morality and respect for human dignity [8-9].

Firstly, the development of digital media technology is analyzed from the macro field to bring changes in the field of art creation, such as animation film and television production and post-production special effects, etc. Literature [10] introduces the development and production of animated films in the context of information technology, which mainly includes the story content design, character selection, distribution and and production process. Literature [11] discusses the complex interactions between people, objects and digital technology in animated filmmaking, and this complex relationship is related to both cross-cultural backgrounds and personal experiences. Literature [12] discusses the rapid development of digital media technology has enriched the artistic expression and artistic content, and focuses on analyzing the practical application of digital media technology in animation film and television post-production special effects production.

In order to adapt to the social demand for animation filmmaking talents, it is necessary to explore the reform and innovation path of animation filmmaking talent training and teaching mode in the information age. Literature [13] evaluates the classroom practice of VR/AR technology in animation teaching, and points out that VR/AR technology promotes students’ motivation to a certain extent, and at the same time, it helps students’ core literacy in film animation. Literature [14] based on film and television animation (FTA) virtual reality teaching experiment design related teaching research can be seen, VR technology to promote the FTA teaching efficiency and students film and television animation (FTA) professional skills knowledge absorption. Literature [15] theoretically analyzes the feasibility of integrating digital media technology into modern animation design and specific paths, emphasizing the positive role of digital media technology in improving the efficiency and quality of animation film production. Literature [16] discusses the application of digital media art in interdisciplinary courses, such as the teaching of film animation courses, art design courses, etc., which provides assistance for the innovative development of digital media art. Literature [17] combined with SOA and VR technology introduced into the animation production course has been to enhance the animation production course interesting and intuitive, to a certain extent, to stimulate the enthusiasm of students’ knowledge learning and the quality of teacher-student interaction. Based on the participatory action research design method, literature [18] examined the role played by the philosophical way of thinking and the tablet tool in the process of animation movie creation, which provides a reference for the teaching reform of animation movie creation course. Literature [19] revealed the teaching practice of animation production course on MOOC platform through questionnaire survey and least squares structural equation modeling, pointing out that students’ attitudes significantly influence behavioral intentions, while perceived behaviors, subjective norms, and attitudes positively influence students’ behavioral awareness. The above study focuses on exploring the enhancement of the teaching effect of movie animation production courses brought by digital technology empowerment, overlooking the cultivation of students’ artistic literacy.

The design intention of this study is to try to apply the 4C/ID model to the teaching of animation film majors, to promote the transformation of the teaching model of animation film majors, and to improve the learning effect and artistic literacy of students. Based on the teaching design steps of 4C/ID model, the teaching mode of animation film major based on 4C/ID model is constructed, and the teaching mode is divided into three parts: example presentation, knowledge learning and evaluation summary. The 4C/ID model is applied to the teaching of animation film majors and the specific teaching effect is tested. The research method used in this paper is mainly the T-test method, which calculates the statistics through the sample values, deduces the probability of the differences, and compares whether the differences between different averages are significant or not. This paper’s animation film professional teaching practice location for C colleges and universities, set up the experimental class and control class and the art literacy training effect of the two comparative analysis, but also on the experimental class within the student’s art literacy difference analysis, to explore the factors affecting the effect of their art literacy training.

2

4C/ID model for teaching the animated film profession

The development of teaching design of animation movie has transformed from orderly design to comprehensive design. The traditional teaching model of animation film majors focuses on cultivating students’ software operation skills, and pays insufficient attention to cultivating students’ comprehensive artistic literacy of software and innovation ability of digital works, while the use of the 4C/ID model can improve students’ comprehensive software operation skills and problem solving skills, and realize the transformation of the teaching model of animation film majors.

2.1

Overview of the 4C/ID model

The 4C/ID model referred to as 4C/ID is also known as Integrated Learning Design [20]. It refers to complex cognitive skills as constituent skills and continues to categorize them into generative and regenerative skills. Regenerative skills are routine aspects of behavior, based on the ability to process rules and can be used repeatedly. Generative skills are the problem-solving, reasoning, and decision-making aspects of behavior.

The 4C/ID model consists of four elements, learning tasks, relevant knowledge, supporting procedures, and specialized drills. Its purpose is to use real-life authentic tasks as the driving force for learning and teaching, to help learners integrate knowledge, skills and attitudes, and to facilitate their transfer of knowledge.

2.2

Instructional Design Steps for 4C/ID Modeling

1)

Step 1, designing complete tasks.

First, design one or more complete learning tasks; then clarify the specific criteria that learners need to meet to complete the task in a standardized manner, i.e., arrange for academic assessment; and then proceed to the sequencing of the learning tasks.

2)

Step 2, Creative level tasks.

In this step, the relevant knowledge is to help the learner to complete the task at the generative level by providing a domain model of the mental schema and a systematic problem-solving approach.

3)

Step 3, Regenerative level tasks.

The regenerative dimension is the opposite of the generative dimension and refers to skills that require proficiency and repetition. Learners are provided with cognitive rules and prerequisite knowledge, as well as corrective feedback through a support program. Specialized practice steps can be added to enable them to reach full proficiency in the skill.

2.3

Characteristics of the 4C/ID model of instructional design

1)

Holistic nature of learning tasks

The 4C/ID model of instructional design requires learners to master a comprehensive set of learning objectives, with the ultimate goal of integrating knowledge, skills and attitudes in a rich, interconnected body of knowledge. When a learner encounters a new scenario, the interconnected body of knowledge that has already been developed helps to activate the various types of knowledge in order to solve the problem. In this model, learners gradually form a comprehensive knowledge system through inductive learning. In order to form a complete cognitive schema, each learning task should be designed to provide learners with a complete task experience.

2)

Complexity of learning tasks

In order to avoid cognitive overload, learners generally complete simple and complete tasks first, and then gradually transition to more difficult complete tasks. At the lowest complexity level, learners will face the simplest tasks that professionals may encounter. At the highest level of complexity, learners will face the most difficult tasks that novices must be able to handle, and in between, multiple levels of complexity may be added to ensure a gradual increase in complexity.

3)

Highly personalized learning

The ordering of learning tasks in the 4C/ID model is dynamic, taking full account of individual learning differences and needs, and realizing a high degree of personalization of learning styles and flexibility of learning tasks. Teachers can establish personalized learning trajectories based on learners’ learning preferences and progress, and provide the best choices and suggestions for independent learning.

2.4

Construction of Teaching Mode of Animation Film Major Based on 4C/ID Model

Based on the above discussion of the design steps and characteristics of the 4C/ID model, this section constructs an IT teaching model based on the 4C/ID model. The teaching model is generally divided into three major parts, namely, the example presentation part, the knowledge and ability learning part and the evaluation and summarization part. 1)

Example Presentation

Before the learning tasks are taught, the teacher first needs to make a comprehensive design for a series of learning tasks. When designing learning tasks, they should be based on specific teaching objectives and clarify the knowledge and skills of the learning domain. A series of tasks should encompass all the knowledge skills from simple to complex, and should take into account the learning objectives and the cognitive level of the students. These learning tasks are based on real situations, closely related to real life, and have the same theme.

2)

Knowledge-based Learning

Knowledge learning includes the learning of creative knowledge and regenerative knowledge. The teacher guides students to analyze the overall logical framework of the example and then inspires them to take the initiative to break down the example. Students initially construct a cognitive schema for accomplishing the task. In order to visualize the cognitive schema, tools such as flowcharts and mind maps can be used to visualize thinking. In the subsequent learning tasks, the teacher should gradually let go of the cognitive schema and allow students to independently reconstruct the cognitive schema and independently complete the drawing of the schema.

3)

Evaluation and Summarization

The evaluation and summarization session is led by the teacher to review the whole learning process. Students independently summarize the knowledges needed to complete the task and conduct reflective evaluation. The summarization of the creative knowledge can allow students to revisit the process of conceptual reasoning according to the drawn schema, so as to further strengthen the mastery of the creative knowledge. Through heuristic questions and answers, students recall the operation points of work preparation and summarize the regenerative knowledges independently.

3

Experimental research on the teaching of animation film specialization based on the 4C/ID model

In order to explore the practical teaching methods and specific teaching effects of the 4C/ID model in the teaching of animation film majors, this chapter will adopt the teaching mode of animation film majors based on the 4C/ID model proposed above to explore the animation teaching practice.

3.1

Study design

3.1.1

Subject of the study

The experiment was conducted in Suzhou City, China, at University C. University C is a comprehensive university with a “dual-track” enrollment strategy, in which some colleges have both undergraduate and specialized programs and enroll both undergraduate and specialized students. In addition, there is also an adult undergraduate program, and the students at College C are diverse in terms of education, age, and major.

Students who did not take digital animation courses were randomly selected as research subjects, and experimental and control classes were set up. There were 60 students in the experimental class and 62 students in the control class.

3.1.2

Research methodology

Hypothesis testing is an important technique [21]. Its application is a method of proof when the original proposition is impossible or difficult to verify. The principle is that, in the case of many experiments that cannot be verified or the cost of verification is very high, the original proposition is proved by using the counterfactual method to falsify its opposing proposition. The basic method is to make relative null hypotheses about the data and the original proposition to be tested. Then through statistical analysis tools, according to its significance index P value, if the rejection of the null hypothesis, the counterfactual is established, that is, the original proposition is proved.

Currently, there have been many hypothesis testing and statistical inference techniques used in teaching and research. The method used in this study is the T-test method [22]. The T-test is to use the T-distribution theory to infer the probability of occurrence of differences, so as to compare whether the difference between two means is significant or not. The steps of the method are as follows. 1)

Unknown μ₁, μ₂, method of testing hypothesis $H_{0} : σ_{1}^{2} = σ_{2}^{2}$ $${H_0}:\sigma_1^2 = \sigma_2^2$$ (1)

Based on the question, formulate the hypothesis to be tested $H_{0} : σ_{1}^{2} = σ_{2}^{2}$ $${H_0}:\sigma_1^2 = \sigma_2^2$$

(2)

Calculate the statistic from the sample values: (1) $s_{1}^{2} = \frac{1}{n_{1} - 1} \sum_{i = 1}^{n_{1}} {(χ_{i} - \bar{χ})}^{2}$ $$s_1^2 = \frac{1}{{{n_1} - 1}}\sum\limits_{i = 1}^{{n_1}} {{{\left( {{\chi_i} - \bar \chi } \right)}^2}}$$ (2) $s_{2}^{2} = \frac{1}{n_{2} - 1} \sum_{i = 1}^{n_{2}} {(y_{i} - \bar{y})}^{2}$ $$s_2^2 = \frac{1}{{{n_2} - 1}}\sum\limits_{i = 1}^{{n_2}} {{{\left( {{y_i} - \bar y} \right)}^2}}$$

Taking the greater of $s_{1}^{2}$ $$s_1^2$$ and $s_{2}^{2}$ $$s_2^2$$ as the numerator and the lesser as the denominator, statistic F is: (3) $F = s_{Big}^{2} / s_{Small}^{2}$ $$F = s_{{\text{Big}}}^2/s_{{\text{Small}}}^2$$

Its numerator and denominator degrees of freedom are ν₁, ν₂. It can be shown that the statistics defined in equation (3), under the condition that assumption H₀ holds, obey a F distribution with degrees of freedom ν₁, ν₂. (3)

From the given significance level α and numerator degree of freedom ν₁ (first degree of freedom), the denominator degree of freedom ν₂ (second degree of freedom) is given in the following equation: (4) $P {F > F_{α / 2} (ν_{1}, ν_{2})} = α / 2$ $$P\left\{ {F > {F_{\alpha /2}}\left( {{\nu_1},{\nu_2}} \right)} \right\} = \alpha /2$$ (5) $P {F > F_{1 - α / 2} (ν_{1}, ν_{2})} = 1 - α / 2$ $$P\left\{ {F > {F_{1 - \alpha /2}}\left( {{\nu_1},{\nu_2}} \right)} \right\} = 1 - \alpha /2$$

$F_{α / 2} (ν_{1}, ν_{2})$ $${F_{\alpha /2}}\left( {{\nu_1},{\nu_2}} \right)$$ can be found from the table of critical values of F distribution, while $F_{1 - α / 2} (ν_{1}, ν_{2})$ $${F_{1-\alpha /2}}\left( {{\nu_1},{\nu_2}} \right)$$ can be obtained according to equation (5). (4)

Judgment

If F > F_a/2 or F < F_1−α/2, the hypothesis is rejected.

If F_α/2 > F > F_1−α/2, the hypothesis is accepted.

Set the significance level α = 0.05, the numerator value of freedom for 7, the denominator degree of freedom for 8, according to the following formula to find F distribution critical value table: (6) $P [F > F_{α / 2} (7, 8)] = α / 2 = 0.025$ $$P\left[ {F > {F_{\alpha /2}}(7,8)} \right] = \alpha /2 = 0.025$$ (7) $P [F > F_{1 - α / 2} (7, 8)] = 1 - α / 2 = 0.975$ $$P\left[ {F > {F_{1 - \alpha /2}}(7,8)} \right] = 1 - \alpha /2 = 0.975$$

Find out F_0.025(7, 8) = 4.53: (8) $F_{0.975} (7, 8) = 1 / F_{0.025} (8, 7) = 1 / 4.9 = 0.2$ $${F_{0.975}}(7,8) = 1/{F_{0.025}}(8,7) = 1/4.9 = 0.2$$

Judgment today F_0.025(7, 8) = 4.53 > F = 1.11 > F_0.975(7, 8) = 0.2, so accept the hypothesis that there is no significant difference between the standard deviation of the two instruments. 2)

Unknown μ₁, μ₂, the method of testing hypothesis $H_{0} : σ_{1}^{2} \leq σ_{2}^{2}$ $${H_0}:\sigma_1^2 \le \sigma_2^2$$ (1)

Formulate the hypothesis to be tested $H_{0} : σ_{1}^{2} \leq σ_{2}^{2}$ $${H_0}:\sigma_1^2 \le \sigma_2^2$$

(2)

Calculate the statistic from the sample values: (9) $F = s_{1}^{2} / s_{2}^{2}$ $$F = s_1^2/s_2^2$$

Here, instead of using $s_{Big}^{2}$ $$s_{{\text{Big}}}^2$$ as the numerator, the estimate $s_{1}^{2}$ $$s_1^2$$ of $σ_{1}^{2}$ $$\sigma_1^2$$ is used as the numerator (i.e., whoever is assumed to be small is used as the numerator). 3)

At a given level of significance α and numerator degrees of freedom ν₁ denominator degrees of freedom ν₂ according to the following equation (10) $P (F > F_{α}) = α$ $$P\left( {F > {F_\alpha }} \right) = \alpha$$

Check the table of F-distribution thresholds to get F_α. 4)

Judgment

If F > F_a, reject the hypothesis; if F ≤ F_a, accept the hypothesis.

3.1.3

Experimental procedure

Before the start of the course teaching, the experimental class and the control class were given a pre-test on the basic level of digital animation and artistic literacy respectively. Then, the curriculum teaching of digital animation was carried out for the two classes separately, with digital animation production as the teaching content. The weekly lesson time of digital animation production for the experimental class and the control class was 1 lesson hour. The course teaching totaled 6 class hours and lasted 6 weeks. The instructors were the same for both classes.

3.2

Digital Animation Course Implementation Process

3.2.1

The process of implementing the teaching model based on the 4C/ID model in the experimental classroom

According to the four elements of the 4C/ID model: learning tasks, related know-how, supporting procedures, and special drills, the experimental class is designed to teach digital animation. By analyzing the teaching materials and organizing and summarizing the related know-how of digital animation, the learning tasks of digital animation series for the experimental class are determined.

3.2.2

The process of implementing the traditional teaching model in control classes

The control class was taught according to the traditional task design and linear teaching model. The traditional teaching model consists of three segments, the example presentation segment, the teaching drill segment and the evaluation and summarization segment. In each learning task, the teacher first presents the example for students to observe. The students imitate the operation and make the example according to the teacher’s lecture. In this process, students internalize the relevant knowledge and skills of digital animation.

4

Analysis of data from the experimental study on the teaching of the animated film program

The results of this experiment were mainly conducted using SPSS AU data analysis software. In this experiment, the independent sample t-test was used to compare the effect of teaching and developing artistic literacy in animation film specialization between the experimental and control classes.

4.1

Comparative Analysis of Artistic Literacy of Students in Experimental and Control Classes

Before and after the experiment, art literacy was measured in the experimental class and the control class respectively. 1)

Comparative analysis of artistic literacy between the experimental class and the control class before the experiment

After the statistical analysis of the recovered data and doing the test of the distribution pattern, the data of the pre-measurement table of the experimental class and the control class are specifically shown in Table 1. It can be seen that the sample skewness of the experimental class and the control class are both lower than 3 in absolute value, and the kurtosis is both lower than 10 in absolute value, although it is not absolutely normal distribution, but it is in line with the characteristics of normal distribution, and can be considered to be approximately in line with the normal distribution.

Table 1.

Distribution pattern inspection

Class	Quantity of samples	Mean	Standard deviation	Degree of bias	Kurtosis
Experimental class	30	35.12	21.08	2.36	6.758
Control class	32	30.44	14.92	2.28	6.577

The results of the pre-test scale independent samples t-test conducted by the experimental and control classes, the data results are shown in Table 2. In this study, independent samples t-test was used to detect and analyze the difference between digital learning and artistic literacy conducted by the experimental and control classes. The data were analyzed to show that students in the experimental and control classes were more likely to use the

Table 2.

Artistic accomplishment

Dimension	Class	Quantity of samples	Mean	Standard deviation	T	P
Use art tools	Experimental class	30	6.48	4.02	1.241	0.223
Use art tools	Control class	32	5.58	3.03	1.241	0.223
Acquire artistic information literacy	Experimental class	30	5.8	3.62	0.953	0.328
Acquire artistic information literacy	Control class	32	5.16	2.95	0.953	0.328
Artistic information literacy	Experimental class	30	6.46	3.96	1.328	0.182
Artistic information literacy	Control class	32	5.44	3.02	1.328	0.182
Artistic accomplishment	Experimental class	30	7.03	4.25	1.385	0.181
Artistic accomplishment	Control class	32	5.94	3.62	1.385	0.181
Artistic immunity	Experimental class	30	5.98	3.77	0.942	0.342
Artistic immunity	Control class	32	5.26	3.2	0.942	0.342
Artistic innovation	Experimental class	30	4.95	2.92	0.861	0.421
Artistic innovation	Control class	32	4.49	2.6	0.861	0.421
Digital learning and artistic literacy	Experimental class	30	36.7	22.54	1.224	0.227
Digital learning and artistic literacy	Control class	32	31.87	18.42	1.224	0.227

P-value is greater than 0.05 in the statistics of the measurement results of the six dimensions of using artistic tools literacy, acquiring artistic information literacy, artistic information literacy, expressing artistic literacy, artistic immunity literacy, and artistic innovation literacy, indicating that the differences between the two classes in these six dimensions are not obvious. The P for the combined dimension of digital learning and artistic literacy is 0.227, which is higher than 0.05, further indicating that there is no significant difference in the level of digital learning and artistic literacy between the two classes.

2)

Comparative analysis of art literacy between the experimental class and the control class after the experiment

The experimental class and the control class were measured and tested on the scale of digital animation production learning and artistic literacy after the experiment. The results of the independent samples t-test of the scale post-test results of digital learning and artistic literacy of the experimental class as well as the control class are shown in Table 3. Using the T-test (all known as independent samples T-test) to study the differences between the experimental class and the control class regarding the seven dimensions, the experimental class and the control class pairs in the six dimensions of digital learning and artistic literacy as well as the total score in a total of seven dimensions of the performance of the experimental class and control class pairs all show significance (P<0.05), which indicates that the experimental class is more than the control class in the degree of the development of the digital learning and artistic literacy is significantly different from that of the control class, and in combination with the mean of the comparison, it was found that the level of artistic literacy of the students in the experimental class was significantly higher than that of the control class first.

Cohen’s d value indicates the magnitude of the difference, with larger values indicating larger differences. The independent samples t-test uses Cohen’s d value to indicate the effect size, and the critical points for differentiation of small, medium and large effect sizes are 0.20, 0.50 and 0.80, respectively. The performance of literacy differences between the experimental class and the control class in each of the dimensions is further analyzed by using Cohen’s d value to compare the performance of the experimental class and the control class in each of the dimensions, and the seven dimensions have higher than a small effect size of 0.50 in the Cohen’s d value, which can be seen that The experimental and control classes exhibited large differences in each of the literacy dimensions.

Specifically analyzing each dimension corresponding to the experimental and control classes, the differences, from highest to lowest, were expressive arts literacy (1.05), digital learning and arts literacy (0.878), arts information literacy (0.857), use of arts tools literacy (0.782), arts literacy (0.755), arts immunity literacy (0.586), and access to arts information literacy ( 0.516). The effect size values of Expressing Art Literacy, Processing Art Literacy, and Digital Learning and Art Literacy all exceeded 0.80. It can be seen that the difference between the experimental and control classes in terms of Expressing Information and Processing Information Literacy and Digital Learning and Art Literacy in general is significant, which indicates that the students of the experimental class have significantly improved in the project learning regarding Art Information Literacy and Expressing Art Literacy and Art Literacy in general.

Table 3.

Independent sample t test of artistic accomplishment

Dimension	Class	Quantity of samples	Mean	Standard deviation	T	P	Cohen’s d
Use art tools	Experimental class	30	11.67	3.83	3.814	0.001**	0.782
Use art tools	Control class	32	9.21	2.41	3.814	0.001**	0.782
Acquire artistic information literacy	Experimental class	30	10.39	3.18	2.465	0.016*	0.516
Acquire artistic information literacy	Control class	32	8.81	2.51	2.465	0.016*	0.516
Artistic information literacy	Experimental class	30	11.21	3.09	4.223	0.003**	0.857
Artistic information literacy	Control class	32	8.78	2.31	4.223	0.003**	0.857
Artistic accomplishment	Experimental class	30	11.64	3.46	5.128	0.002**	1.05
Artistic accomplishment	Control class	32	8.63	1.99	5.128	0.002**	1.05
Artistic immunity	Experimental class	30	10.24	3.38	2.834	0.005**	0.586
Artistic immunity	Control class	32	8.78	2.11	2.834	0.005**	0.586
Artistic innovation	Experimental class	30	8.4	2.37	3.652	0.008**	0.755
Artistic innovation	Control class	32	6.91	1.59	3.652	0.008**	0.755
Digital learning and artistic literacy	Experimental class	30	63.55	16.3	4.325	0.007**	0.878
Digital learning and artistic literacy	Control class	32	51.12	11.05	4.325	0.007**	0.878

At the end of the experiment, a quiz was also launched for the experimental and control classes, and the test scores of the experimental and control classes were statistically analyzed using the independent samples t-test. The data was analyzed as shown in Table 4. Using the t-test (i.e., independent samples t-test) to investigate the differences between the experimental and control classes for the total score of the information technology test scores for a total of 1 item, the digital animation test scores showed significance p<0.01 in both the experimental and control classes, which indicates that there is a direct difference between the two samples. As the total score showed significant difference at 0.01 level (P=0.003, T=3.118), combined with the specific differences, it was known that the mean value of the experimental class was 76.28, which was higher than the mean value of the control class of 67.62. It can be seen that: both samples of information technology test scores showed significant variability, and the data of the test of information technology knowledge were improved to different degrees, and the experimental class performed better than the control class. Through the Cohen’s d value to expand the comparison of the magnitude of difference, Cohen’s d value is 0.651, greater than 0.50 less than 0.80, indicating that the achievement of the magnitude of difference is larger, indicating that there is no delay in the learning of knowledge related to digital animation production.

Table 4.

Digital animation test

Class	Quantity of samples	Mean	Standard deviation	T	P	Cohen’s d
Experimental class	30	76.28	11.5	3.118	0.003**	0.651
Control class	32	67.62	14.24	3.118	0.003**	0.651

4.2

Differential Analysis of Artistic Literacy of Students in Experimental Classes

In this section, we will further analyze the differences in artistic literacy among the students within the experimental class, and explore the influence of the students’ academic qualifications, majors and other factors on the effectiveness of their artistic literacy cultivation. The basic information of the students in the experimental class is shown in Table 5.

Table 5.

Basic information of students

-	Categories	Number of students	Total
Majors	Art major	20	60
	Technical major	22
	Major in humanities and social sciences	18
Educational background	Junior college	15
	Undergraduate	6	60
	General undergraduate	29
	Master’s degree	10

1)

Analysis of artistic literacy of students with different academic qualifications

The art literacy mean scores of the experimental class students with different academic qualifications are specifically shown in Table 6. The mean scores in descending order are M=4.01 (master’s degree and above), M=3.91 (adult undergraduate), M=3.87 (general undergraduate), and M=3.66 (junior college). Students with a master’s degree or higher had the highest artistic literacy scores, and students with a college degree had the lowest scores.

Table 6.

The artistic accomplishment of students with different academic qualifications

Record of formal schooling	Quantity of samples	Mean	Standard deviation	F	P
Junior college	15	3.66	0.56	8.26	0.028*
Adult undergraduate	6	3.91	0.46
Ordinary undergraduate	29	3.87	0.43
Master ‘s degree or above	10	4.01	0.47

Multiple comparisons were made between the artistic literacy of students with different academic qualifications, and the results are specifically shown in Table 7. The results of multiple comparisons show that there is a significant difference in artistic literacy between students whose academic qualifications are junior colleges and students with all other academic qualifications, and there is no significant difference in artistic literacy between students whose academic qualifications are adult undergraduate, general undergraduate, master’s degree and above.

Table 7.

Multiple comparison results of students’ artistic literacy

-	Junior college	Adult undergraduate	Ordinary undergraduate	Master ‘s degree or above
Junior college	-	0.00**	0.02*	0.05*
Adult undergraduate	-	-	0.62	0.91
Ordinary undergraduate	-	-	-	0.66
Master ‘s degree or above	-	-	-	-

2)

Analysis of art literacy of students in different majors

The mean scores of artistic literacy of students in experimental classes of different majors are specifically shown in Table 8. The mean scores of art majors, humanities and social sciences majors, and science and technology majors in descending order, corresponding to the mean values of 3.93, 3.71 and 3.59, respectively, indicate that students majoring in art majors have the highest scores of artistic literacy level, and students majoring in science and technology majors have the lowest scores of artistic literacy level.

Table 8.

The artistic accomplishment of students of different majors

-	Quantity of samples	Mean	Standard deviation	F	P
Art majors	20	3.93	0.47	6.58	0.017
Humanities and social sciences majors	22	3.71	0.24
Science and engineering majors	18	3.59	0.57

The results of the multiple comparisons of the artistic literacy of students in different majors are shown in Table 9. Multiple comparisons between groups were conducted and it was found that there was a significant difference in the level of artistic literacy between students majoring in arts and those majoring in other types of majors. There is no significant difference in artistic literacy between students majoring in science and engineering and those majoring in humanities and social sciences.

Table 9.

Multiple comparison results of the artistic accomplishment of different majors

-	Art majors	Humanities and social sciences majors	Science and engineering majors
Art majors	-	0.01*	0.03*
Humanities and social sciences majors	-	-	0.83
Science and engineering majors	-	-	-

Overall, the p-values of the ANOVA between the students in the experimental classes with different academic qualifications and majors are less than the 0.05 level of significance, indicating that there are significant differences in the results of the inter-group comparisons between the students with different academic qualifications and majors.

5

Conclusion

In order to realize the transformation of the teaching model of the animation film profession, this paper constructs the teaching model of the animation film profession based on the 4C/ID model and applies it to the teaching practice of the animation film profession to test its specific teaching effect and analyze the effect of the students’ artistic literacy cultivation. The experimental objects of the teaching practice of animation film major are students of C university, and the experimental class and the control class are set up for comparison and analysis.

Before the experiment, the P-values of the experimental class and the control class in the six dimensions of artistic literacy such as using artistic tools literacy, acquiring artistic information literacy, etc. are all greater than 0.05, indicating that there is no significant difference between the two classes in the level of artistic literacy before the experiment. After the experiment, all of the six dimensions of artistic literacy and the integrated dimensions of digital learning and artistic literacy between the experimental class and the control class showed significance (P<0.05), and the level of artistic literacy of the students in the experimental class increased significantly compared to the control class. The performance of the difference between the two was further analyzed by Cohen’s d value, which was greater than the small effect size of 0.50 for all dimensions, proving that the experimental class and the control class showed a large difference in each dimension of artistic literacy. In the postexperimental digital animation quiz, the mean value of the experimental class reached 76.28, which was higher than that of the control class by 8.66, showing a significant difference at the 0.01 level.

The variability of students’ artistic literacy within the experimental class was analyzed to explore the factors affecting the effect of artistic literacy development. The mean value of artistic literacy of students in the experimental class with different academic qualifications varied, with the highest mean value of 4.01 for master’s degree and above, followed by adult undergraduate (M=3.91), general undergraduate (M=3.87), and junior college (M=3.66). Further multiple comparisons showed that there was a significant difference in artistic literacy between students with college degree and all other degrees, while there was no situation of difference between students with other degrees. Among the students of different majors, the highest mean value of artistic literacy is 3.93 for art majors, and the mean values of humanities and social sciences majors and science and technology majors are 3.71 and 3.59. Multiple comparisons show that there is a significant difference in the level of artistic literacy among art majors compared to students of other majors, while there is no significant difference between humanities and social sciences majors and science and technology majors. Accordingly, it can be judged that the students’ education and majors are the influencing factors of the differences in the effect of art literacy development.

Language:: English

Publication timeframe:: 1 times per year
Journal Subjects:: Life Sciences, Life Sciences, other, Mathematics, Applied Mathematics, General Mathematics, Physics, Physics, other

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Digital Technology-Driven Transformation of Teaching Model in Animation Film Program and Enhancement of Students’ Artistic Literacy

Zhexi Yao

Published Online: Sep 26, 2025

Received: Jan 12, 2025

Accepted: May 04, 2025

DOI: https://doi.org/10.2478/amns-2025-1050

Keywords4C/ID model, T-test method, Digital technology, Teaching animation film majors

© 2025 Zhexi Yao, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Keywords
4C/ID model, T-test method, Digital technology, Teaching animation film majors