A Study of the Effectiveness of Blended Teaching Models for Accounting Majors

The so-called “blended teaching” refers to a teaching mode that utilizes the advantages of both traditional and online teaching in combination with “online + offline”. Based on the characteristics of the course and teaching needs, it not only retains the teacher guidance and face-to-face interaction between teachers and students in traditional teaching, but also relies on the mobile Internet to achieve the extension of the classroom to the after-school and extracurricular activities, and enhances the online interaction and communication, learning evaluation and feedback to improve the quality of teaching and enhance the teaching effect. Blended teaching has been widely used in college teaching [1–5]. The accounting major is boring. At present, the teaching of accounting majors in most colleges and universities still mainly revolves around “books”, from the introductory knowledge of accounting to the basics of accounting practice, and teachers are accustomed to spending more classroom time on the “explanation” of knowledge points, rather than focusing on the “understanding” of students. Sign-in, explanation, random questioning, and examination have become common modes in the daily classroom of accounting majors in colleges and universities [6–9]. Although many colleges and universities combine extracurricular practice during winter and summer vacations to increase students’ practical experience opportunities, many teachers also lack the practice of accounting positions, and are accustomed to “marking key points” and “repeating memorization”, unable to guide knowledge points with rich and diverse examples, and the occlusion of the teaching environment also makes the teaching process too “rigid” [10–11]. Vigorously promoting education informatization is an important way to help the reform and development of accounting education. Accounting majors should break the traditional lecture-based teaching mode, combine the characteristics of accounting majors, give play to the advantages of online teaching, integrate teaching resources, choose the appropriate teaching platform, and apply the blended teaching mode to teaching [12–15]. At the same time, teachers should play the main role of students, conduct guided learning, let students take the initiative to find problems, solve problems, and use the relevant teaching platform to arrange learning tasks, do a good job of answering questions and solving problems, so as to improve the quality of teaching [16–19].

This paper innovates the way and method of teaching accounting, and designs a blended teaching model for accounting majors that includes all aspects of pre-course, in-course, and post-course based on constructivist principles. Taking bookkeeping vouchers as an example, the implementation process of blended teaching is decomposed in detail. Teaching experiments were conducted in two accounting major classes, and lagged sequence analysis was first introduced to construct a coding table to analyze the ratio of teacher-student behaviors, teacher’s questioning and students’ speeches, teacher’s verbal roles, technology use behaviors, types of teacher-student interactions, and treatment of abnormal behaviors under the blended teaching mode. Then compare and examine the final grade of the experimental group under the blended teaching mode and analyze the learning attitude and accounting literacy of the two classes in order to test the effectiveness of the blended teaching mode of accounting majors.

2

Method

2.1

Design of blended learning model

2.1.1

Instructional design process

This paper constructs the following blended teaching mode process framework for accounting majors, as shown in Figure 1. The process of blended teaching mode for accounting majors is mainly composed of three parts, namely, independent learning before class, discussion and exchange and Q&A during class, and consolidation and improvement after class. The specific content of the blended teaching model process for accounting majors will be analyzed and discussed in the following section.

2.1.2

Design of blended learning model

The main supporting theories of blended teaching are constructivist learning theory and behaviorist learning theory, which encompasses three parts of the teaching process: before, during and after class, as shown in Figure 2 below:

1)

Independent study before class

Combined with the content of constructivist learning theory and behaviorist learning theory, it can be seen that in the specific teaching practice, the teacher should be the guide of the construction of students’ knowledge system, while the students are the main body of the information construction, which emphasizes the initiative of the students’ knowledge construction and strengthens or corrects the students’ learning behavior. Therefore, in the pre-course independent learning link of the blended teaching mode of secondary accounting, the teacher should strive to build a good independent learning situation for students, cultivate and enhance the independent learning ability of students in secondary schools and colleges, and change the students’ inherent thinking, so that they can become the active constructor of knowledge rather than the passive recipient of information [20].

After completing the design of the blended teaching process, teachers need to familiarize themselves with the functions of the Blue Ink Cloud Class, so as to efficiently complete the production and uploading of teaching resources. The production of teaching resources may bring certain adjustments to the teachers of the traditional teaching mode, which should not only take into account the requirements of the teaching objectives, but also need to take into account the requirements of the Blue Ink Cloud Class platform for the size, clarity and format of the teaching resources, as well as taking into account the preferences of the students. The online teaching resources for the blended teaching mode of accounting in secondary schools should have the following characteristics, as shown in Figure 3.

2)

Interactive Q&A session in class

Constructivism emphasizes that in the process of teaching, we should pay attention to the students’ inherent knowledge reserves, and should not use simple “duck” teaching, but actively guide the construction of students’ knowledge system. This is also true for the blended teaching of secondary accounting majors, which should adopt a variety of teaching methods and combine with the online teaching interactive module of the Blue Ink Cloud Class to cultivate students’ interest in learning and their ability to learn actively. The interactive mode of answering questions in class effectively balances the advantages of traditional and online teaching modes.

3)

Consolidation and improvement after class

Constructivist learning theory emphasizes the interactivity of the learning process, and believes that the learning process should include the cooperation and communication between students and teachers as well as the sharing of resources. In order to consolidate and improve the blended teaching mode after class, it is important to emphasize communication and collaboration between teachers and students. Students need to check their knowledge in the classroom after class to make up for the deficiencies and “learn from the past to know the new”.

2.1.3

Evaluation of teaching and learning

For the teaching evaluation of the blended teaching mode of the accounting profession, this paper divides it into two aspects: process evaluation and summative evaluation. Both account for 60% and 40% of the total score, respectively. Among them, process evaluation is carried out throughout the entire mixed teaching mode for secondary school accounting majors, which is mainly used to measure and evaluate the Blue Ink Cloud Classroom platform. In the specific teaching evaluation, the teacher plays the role of the master and actively guides the students to carry out self-assessment and mutual assessment between students or groups. Students gain experience by participating in the online learning activities of the Blue Ink Cloud Class Platform, and after the end of the lesson, the scores of students in each functional module can be summarized, and the final online scores of students can be calculated according to the proportion of online scores in each module.

2.2

Teaching and Learning Process - Take “Bookkeeping Voucher” as an Example

2.2.1

Online Exploration: Completion of Preliminary Tasks

1)

Production and uploading of teaching resources

According to the overall design of teaching, the pre-course task list, courseware and teaching video of bookkeeping vouchers were produced. Uploaded to the resource library through the Blue Ink Cloud Class platform, the videos were partly self-made and partly selected from websites such as China Mucous, Wisdom Vocational Education and National Vocational Education Teaching Resource Base, with appropriate additions and deletions of content so that students could clearly understand the learning content before class. At this time, students have joined the Basic Accounting course, and teachers need to urge students to prepare for the course carefully. Teaching resources mainly include contextual videos, pre-course task lists, PPT courseware, microclasses, test questions, brainstorming and so on.

2)

Release the list of independent learning tasks

The implementation of the task-driven blended teaching mode research needs to take full account of the students’ individualized needs and basic differences, and carry out the design of the blended teaching process of secondary accounting majors in response to the students’ actuality. When conducting accounting courses, it is necessary to have certain requirements for each individual’s knowledge level, which leads to significant variability among most students. In view of this situation, teachers should focus their attention on all the students in the class, tailor their teaching to the different conditions of the students, and assign work that emphasizes both the basic nature and the extended nature.

Groups were divided before the class. In order to avoid too large a gap between the ability of the members of the group, affecting the learning effect of the students, the members of the group in a “2 + 4” combination, the teachers in accordance with the end of the previous semester’s grade list, select a good foundation and a relatively weak foundation of the students as the original members of the group, the two students to find their own four other students to form a complete group. The class is divided into seven groups, and each group elects a leader.

Students logged into the Blue Ink Cloud classroom and found the list of pre-class tasks in Resources. Submit four basic tasks and one extension task as required. Teachers can view the students’ test results on the cloud class platform, analyze the students’ pre-testing, identify common and individual problems, and plan for teaching and explaining points in the class beforehand.

3)

Student pre-study feedback teacher summary

Collect and summarize the bookkeeping voucher filling problems, students encountered in the process of self-study and the completion of the task of the students to understand the student learning situation, in order to prepare for the next step in classroom teaching.

2.2.2

Interaction in the classroom: unfolding blended learning

1)

Q&A and contextual introduction

Before the lesson, each group has summarized the group members in the self-study process of the doubts and problems, the class in the form of a group by the leader of each group to the teacher to ask questions. First of all, the teacher of the students raised questions and pre-course feedback on the problem of Q&A, and secondly, through the playback of the context of the video “bookkeeping vouchers of the correct approach” and “bookkeeping vouchers to fill out” micro-lesson content, which triggered students to think about the bookkeeping, most students are Most of the students were attracted by the video. After the end of the video, the classroom atmosphere was active and the response was enthusiastic. Everyone began to discuss the content of the video and express their own views. In the process of communicating with students, the teacher encouraged them to keep more accounts in general, which is also a form of financial planning to improve their planning ability.

2)

Tasks: consolidation of theoretical knowledge training

Task one before class has been released through the task list, including the content of bookkeeping vouchers and other conceptual content, the part of the content of the examination of the students’ understanding of pre-course learning, need to independently solve the task one, so that students have a deeper understanding of the basics of the class to give students fifteen minutes to complete. Teachers utilized this time to step off the stage and make rounds to enhance supervision and management of students, encouraging students to learn effectively and keeping the class in order. At the same time, they pay attention to the learning progress and learning status of each group, keep good grading records, observe the students’ mastery of the “contents of bookkeeping vouchers”, and provide necessary assistance.

3)

Teaching the key points and difficulties to sort out again

Through the “pre-study - cooperative inquiry - teacher sorting” three rounds of learning, most students can master the knowledge and skills of this section, but we can not rule out the existence of individual students still have personalized problems. For this reason, the teacher carries out the final summary and sorting. Teachers according to the completion of the task, the key points and the operation of the essentials of combing again, while filling out the vouchers while explaining the error-prone places, mainly in the form of animation will be the content of the vouchers and fill out the specific requirements of one by one presentation. At the same time, let the students find out how to fill in the wrong bookkeeping vouchers to pause, so that they can check and correct errors, and constantly consolidate.

2.2.3

Post-course development: promoting deeper learning

1)

After-class review and test completion

The review and consolidation after class is mostly carried out through homework, which can be arranged as practical problems, multiple-choice questions, and fill-in-the-blank questions. Blue Ink Cloud Class is used for pushing, which is helpful for teachers to grasp the students’ homework situation in time and adjust the key points and difficulties of classroom learning. Summarizing and reflecting after class helps improve the learning effect, which is conducive to the establishment of complete and clear concepts in the knowledge system of students. For some students who do not have a good grasp of the knowledge points, teachers need to give them more attention and guidance. After the lesson, it is necessary for them to verify if their learning effect has met the requirements. Students need to complete the tasks set by the teacher independently, take a picture of the answers on paper, or do the homework online for the teacher to judge.

2)

Push practical development videos

Teachers in the MOOC, intelligent vocational education and other platforms to select in line with the cognitive level of students and lively and interesting video as part of the content, in the bookkeeping vouchers in this section, including “financial various types of payment documents design” “financial figures in the how to write 0” “Amount and date writing specifications” ‘binding of accounting vouchers’ and other practical expansion of the video. Let the students who have the ability to learn more about the accounting process, in the teaching content more relevant to the actual case of the enterprise, to enhance the enthusiasm of the students on the practice of manual accounts to cultivate students’ interest in learning.

2.3

Lagged Sequence Analysis

2.3.1

Overview of the lagged series analysis approach

LSA has good application prospects in the field of learning behavior analysis, which can help researchers and pedagogues accurately grasp the potential behavioral patterns of learners, explain the reasons for technology-enhanced learning from a behavioral perspective, and effectively guide the design and implementation of subsequent teaching and learning activities.

The current software for analyzing user behavior mainly includes Intelligent Miner from IBM, Enterprise Miner from SAS, and so on. Although the functions of these software are powerful, they are often complicated to use, require a certain level of professional experience, and are difficult to quickly master by most researchers. In order to conveniently and effectively assist with behavioral data processing, Bakeman and Quera collaborated to develop GSEQ (General Sequential Querier), a dedicated software for interaction behavior analysis. This software simplifies the behavioral analysis process, improves the data processing efficiency, and also promotes the promotion of LSA applications in various fields.

The main process of applying GSEQ software to analyze the behavioral sequence patterns of online learning includes (1) inputting all behavioral codes in the format required by GSEQ; (2) compiling the system and generating the MDS file; (3) checking the Kappa consistency of the behavioral codes (for the codes completed by more than one person); (4) performing the behavioral sequence analysis to get the behavioral conversion frequency table and the adjusted residual table; and (5) Filter the behavioral sequences with significant meaning according to the adjusted residual table, and plot the behavioral transition maps.There are some precautions in the operation of GSEQ. First, it is necessary to define the codes of all behaviors in Event, and undefined codes cannot be used for behavior coding. Secondly, the codes should be categorized in the order in which the behaviors occur and entered into the control window in accordance with the format requirements of GSEQ. Finally, the sequence analysis should be performed by selecting the Compute Table Stats function under the Run menu and checking Adjusted Residual (z).

2.3.2

Behavioral sequence analysis formulas

1

Z_{j} = \frac{x_{i j} - E_{i j}}{\sqrt{E_{i j} (1 - P_{i}) (1 - P_{j})}}

2

E_{i j} = \frac{\sum_{i} x_{i j} \sum_{j} x_{i j}}{\sum_{i} \sum_{j} x_{i j}}

3

P_{i} = \frac{\sum_{i} x_{i j}}{\sum_{i} \sum_{j} x_{i j}}

4

P_{j} = \frac{\sum_{j} x_{i j}}{\sum_{i} \sum_{j} x_{i j}}

x_ij : frequency of switching from behavior i to behavior j.

p_i : probability of switching from behavior i to other behaviors.

p_i : probability of switching from behavior j to other behaviors.

E_ij : Expected value of switching from behavior i to behavior j.

According to formula (2) (3) (4) and finally (1), the z value is obtained to determine the significance of the behavior i. In this paper, the significance level is set at 0.05 and a one-tailed test is used, then the transfer of the behavior can be considered significant when the z value is greater than 1.96. Finally, it can be plotted as a behavioral transfer matrix to visualize the z values to present the analysis results, and it can also be plotted as a state-behavioral transfer chart to show the significant behavioral transfers more intuitively [21].

2.3.3

Data analysis methods

The t test is primarily used for normally distributed information with a small sample size (e.g., n < 30) and an unknown overall standard deviation σ. The t test is a test used for the degree of difference between two means of a small sample. It uses the t distribution theory to infer the probability of a difference occurring and thus determine whether the difference between two means is significant or not [22]. Three main methods are included: single-sample t test, paired-sample t test and two-independent-sample t test. In this paper, the paired-sample t test is applied to analyze the systematic errors between the two laboratories.

The basic idea of the Paired Samples t test is to set up a population X₁ obeying the normal distribution N(μ₁,σ₁₂) and a population X₂ obeying the normal distribution N(μ₂,σ₂₂), and to draw samples (x₁₁, x₁₂,⋯,x_1n) and (x₂₁, x₂₂,⋯,x_2n) from these two populations, respectively, and to pair the two samples with each other. It is required to test whether μ₁ and μ₂ are significantly different. Specific steps are as follows: 1)

Introducing a variable

Introduce a new random variable Y = X₁ – X₂, corresponding to the sample value (y₁, y₂,⋯,y_n), where y_i = x_1i – x_2i(i = 1,2,⋯, n).

2)

Establish the hypothesis

H₀ : μ_r = 0 (there is no systematic error in the data measured by the two laboratories).

3)

Calculate the formula and its significance: 5 $t = \frac{\bar{y}}{\frac{S_{y}}{\sqrt{n}}}$ where: $\bar{y} = \frac{\sum_{i = 1}^{n} y_{i}}{n}$ - the average of the paired sample differences.

$S_{y} = \sqrt{\frac{\sum_{i = 1}^{n} {(y_{i} - \bar{y})}^{2}}{n - 1}}$ - standard deviation of the paired-sample difference.

n - the number of paired samples.

This statistic t obeys a t distribution with n–1 degrees of freedom under the condition that the null hypothesis (μ_r = 0) is true.

3

Results and Discussion

A teaching experiment was conducted for its one semester in an accounting program in a university, and an accounting professional exam was administered as a pre- and post-test before the beginning and after the end of the semester, respectively. In the teaching practice, lagged sequence analysis was first used to further explore the sequence of teacher-student interaction behaviors that reached the level of significance in the blended learning environment.

3.1

Behavioral sequence analysis of teacher-student interaction

The study used lagged sequence analysis to further explore the sequence of teacher-student interaction behaviors that reached significance in the smart classroom environment.

The frequency of coded behaviors is as follows:

T1: Teacher acceptance of emotions, T2 Teacher encouragement of praise, T3 Adoption of opinions, T4 Asking open-ended questions, T5 Asking closed-ended questions, T6 Teaching, T7 Instructing, T8 Criticizing, S1 Responding (passive response), S2 Responding (active response), S3 Active questioning, S4 Discussing with peers, O1 Confusion that does not contribute to teaching, O2 Thinking about the problem, O3 Doing the exercise, TT Teacher manipulating the technology, ST Student manipulating the technology, and TS Technology acting on the students. Technique, ST Student manipulation technique, TS Technique acting on students.

Behavioral sequence refers to the conversion order between the initiating behavior and the accompanying behavior, such as the teacher’s question (T5) coding immediately after the appearance of the student’s response (S1) coding, the corresponding behavioral sequence is T5 → S1. According to the behavioral coding data, the use of the GSEQ software to produce a behavioral conversion frequency table, the results are shown in Table 1, in which the first column represents initiating behaviors, the first line represents accompanying behaviors, and the numerical values in the table represent the behavior conversion frequency. Each cell on the diagonal (top left to bottom right) in Table 3 is called a steady state cell, indicating that a certain behavior occurs continuously, i.e., the same behavioral category occurs continuously for more than 3 seconds.

Table 1.

Behavioral conversion frequency table

	T1	T2	T3	T4	T5	T6	T7	S1	S2	S3	S4	O1	TT	ST	TS
T1	3	2	0	1	4	4	2	1	2	2	3	1	2	1	0
T2	0	14	0	0	-1	1	6	1	1	0	1	1	1	2	2
T3	1	0	3	3	0	2	1	2	1	2	0	0	3	2	0
T4	2	1	2	5	1	2	1	1	1	0	2	2	1	1	0
T5	2	1	0	1	3	5	10	4	1	2	2	2	2	1	2
T6	2	0	2	3	7	65	8	0	2	3	1	1	10	3	1
T7	2	2	1	0	3	7	44	4	7	0	5	16	11	10	2
S1	3	1	0	3	2	3	2	6	4	0	2	0	2	2	0
S2	2	1	1	2	3	1	1	1	74	1	1	1	2	2	0
S3	2	0	4	1	0	5	1	1	2	3	0	1	0	1	1
S4	2	1	0	0	1	1	1	0	0	2	64	1	1	15	0
O1	0	3	1	0	0	4	9	1	3	0	2	43	9	2	0
TT	3	1	3	1	6	7	12	3	1	6	1	7	111	1	3
ST	0	1	1	2	4	4	9	0	2	2	12	2	1	186	1
TS	1	2	0	1	1	2	0	2	0	1	0	1	2	1	10

The frequency of behavioral transitions shows that there is a persistent occurrence of teachers’ praising behavior (T2), lecturing behavior (T6), and instructing behavior (T7), students’ active responding behavior (S2), communicating with their peers (S4), disorganized behaviors that do not contribute to teaching and learning (O1), and technology-using behaviors (TT, ST, and TS). In addition to this, there were many behaviors that switched more frequently, even more frequently than on the diagonal; for example, the S4→ST switch occurred 15 times and the TT→T7 switch occurred 11 times. However, this is not enough to indicate that these behavioral transitions need to be taken seriously, and significance verification of these behavioral transitions is also needed.

Table 2 shows the adjusted residual table generated using GSEQ software, from which the residual parameter (z) of all behavioral sequences can be known. If the value of z is greater than 1.96, it means that the behavioral sequence has reached a significant level, such as the behavioral sequence T1→T5 has a z value of 3.26, which has reached a significant level.

Table 2.

Adjusted residue table

Z	T1	T2	T3	T4	T5	T6	T7	S1	S2	S3	S4	O1	TT	ST	TS
T1	5.28**	-0.7	-0.45	-0.72	3.26**	-0.44	-0.59	-0.74	-0.7	-0.55	-0.54	-0.63	-0.94	-0.56	-0.43
T2	-0.57	24.33**	-0.81	-0.85	-0.58	-0.34	-0.36	-0.39	-0.62	-0.6	-0.98	-0.5	-0.82	-0.9	-0.59
T3	-0.38	-0.49	3.18**	2.69*	1.68	-0.63	-0.78	-0.59	-0.47	2.88*	-0.42	-0.8	-0.85	-0.71	-0.32
T4	-0.31	-0.58	-0.42	9.76**	-0.89	-0.42	-0.45	-0.91	-0.68	-0.86	-0.47	-0.91	-0.81	-0.49	-0.79
T5	-0.54	-0.95	-0.91	-0.5	2.95**	-0.8	6.54**	6.83**	-0.91	-0.48	-0.37	-0.44	-0.48	-0.82	-0.32
T6	-1.18	-0.88	-0.6	0.85	2.64**	18.37**	-0.37	-0.99	-0.52	-0.94	-0.41	-0.82	-0.52	-0.69	-0.46
T7	-0.29	-0.43	-0.57	-0.72	0.89	-0.5	10.28**	2.36*	-0.75	-0.53	-0.53	2.98**	-0.44	-0.47	-0.64
S1	2.35*	-0.91	1.34	2.33*	-0.96	-0.58	-0.51	7.18**	-0.95	-0.66	-0.56	-0.79	-0.88	-0.69	-0.51
S2	3.19**	-0.46	15.39**	-0.36	-0.82	-0.51	-0.98	-0.95	25.48**	-0.49	-0.9	-0.91	-0.97	-0.81	-0.82
S3	2.48*	-0.43	-0.66	-0.89	-0.43	-0.71	-0.76	-0.57	-0.95	5.79**	-0.8	-0.67	-0.67	-0.9	-0.8
S4	0.05	-0.81	-0.76	-0.41	-0.59	-0.55	-0.55	-0.73	-0.93	-0.42	23.56**	-0.61	-0.74	-0.43	-0.93
O1	-1.96	-0.89	-0.32	-0.84	-0.54	-0.59	-0.57	-0.76	-0.45	-0.54	-0.6	16.34**	-0.97	-0.33	-0.6
TT	-0.44	-0.69	-0.35	0.08	-0.89	-0.97	-0.4	-0.48	-0.93	-0.84	-0.58	-0.82	20.81**	-0.6	-0.89
ST	-1.36	-0.76	-0.59	-0.43	-0.79	-0.62	-0.68	-0.65	-0.95	-0.92	-0.43	-0.61	-0.98	24.35**	-0.88
TS	-0.85	-0.87	-0.47	-0.31	1.12	-0.75	-0.93	-0.69	-0.39	-0.48	-0.81	-0.73	-0.84	-0.45	25.35**

According to Table 2, a behavioral sequence transformation diagram is drawn, as shown in Figure 4. Where the arrow points to the accompanying behavior, the value and thickness of the connecting line represents the residual parameter of the behavioral sequence, the larger the z-value, the thicker the connecting line, the higher the level of significance of the behavioral sequence. As can be seen from Figure 4, in addition to the 15 significant behavioral sequences that point to themselves, there are also 13 other significant behavioral sequences, which together reflect the laws and characteristics of teacher-student interaction behavior. By analyzing these significant behavioral sequences, it can help teachers reflect on classroom teaching and promote accounting professional development.

3.2

Analysis of the results of teaching experiments

3.2.1

Analysis of data on final examination results

The final examination is divided into two parts: theory examination and practical examination, both worth 50 points, with a total score of 100 points. The specific statistical analysis is shown in Table 3.

Table 3.

Final assessment results

	Group	Case number	Mean value	Standard deviation	Standard error mean
Theory	Experimental group	50	35.97	3.006	0.55
Theory	Control group	50	33.04	4.79	0.625
Practical operation	Experimental group	50	40.82	3.508	0.426
Practical operation	Control group	50	36.17	2.876	0.801
Total score	Experimental group	50	76.79	4.19	0.609
Total score	Control group	50	69.21	3.551	0.378

Whether it is the theory exam, practical exam, or total score, the experimental group is higher than the control group. Especially in the practical exam, the experimental group is 4.65 points higher than the control group.

Table 4 shows the results of independent samples t-test for final examination results.

Table 4.

Final examination results of the independent sample t test

		Levin variance equivalence test		Average equivalent t test
		F	Sig.	t	df	Sig. (Double)	MD	SED	95% confidence interval
		F	Sig.	t	df	Sig. (Double)	MD	SED	Down	Up
Theory	Assumed equal variance	0.004	0.956	3.167	99	0.003	2.93	0.842	0.971	4.329
Theory	Unassuming equal variance			3.167	81.258	0.003	2.93	0.842	0.971	4.329
Practical operation	Assumed equal variance	6.275	0.018	3.554	99	0.002	4.028	1.137	1.778	6.275
Practical operation	Unassuming equal variance			3.554	72.833	0.002	4.028	1.137	1.772	6.279
Total score	Assumed equal variance	7.852	0.007	4.781	99	0	6.68	1.397	3.905	9.452
Total score	Unassuming equal variance			4.781	74.568	0	6.68	1.397	3.892	9.463

It can be seen that the significance of Levine’s variance equivalence test for theoretical grades, practical grades and total grades is greater than 0.05, with reference to the first article of the t-test, the significance of their t-tests (two-tailed) is less than 0.05 and the difference 95% confidence intervals do not include 0. It can be concluded that there is a significant difference between experimental and control groups in terms of theoretical grades, practical grades and total grades.

To summarize, in terms of final examination scores, the experimental group is comprehensively better than the control group, and the difference is obvious. In the assessment of basic theoretical knowledge, the average score of the experimental group is higher than that of the control group by about 2 points, which proves that the application of the hybrid instructional design mode to accounting classroom teaching can enable students to intuitively understand the situation of accounting accounts, enhance the in-depth understanding of the theoretical knowledge of accounting, break through the teaching difficulties, and help students master the basic concepts and basic knowledge of accounting. In terms of practical skills assessment, the average score of the experimental group is about 4 points higher than that of the control group, indicating that the hybrid accounting environment helps to promote the improvement of students’ practical skills. Hybrid online teaching, as an auxiliary tool in the teaching process of students, moves the real accounts of different industries into the platform, utilizes virtual simulation technology to reproduce various scenarios in accounting work, adopts situational teaching method, creates appropriate work scenarios, and utilizes functions such as role transformation, onboarding operation, and business route selection, so that students can improve their practical skills through practice.

3.2.2

Analysis of Learning Attitude and Accounting Literacy Posttest Data

The statistical results of the learning attitude and accounting literacy posttest groups are shown in Table 5. Table 6 shows the results of the independent samples t-test for learning attitude and accounting literacy post-test.

Table 5.

The study attitude and the statistical results of the post-evaluation group

	Group	Case number	Mean value	Standard deviation	Standard error mean
Learning attitude	Experimental group	50	57.84	2.913	0.432
Learning attitude	Control group	50	49.15	4.494	0.493
Accounting	Experimental group	50	40.96	4.744	0.803
Accounting	Control group	50	34.28	3.262	0.856

Table 6.

Test results of independent sample test after learning attitude and evaluation

		Levin variance equivalence test		Average equivalent t test
		F	Sig.	t	df	Sig. (Double)	MD	SED	95% confidence interval
		F	Sig.	t	df	Sig. (Double)	MD	SED	Down	Up
Learning attitude	Assumed equal variance	0.15	0.917	3.524	98	0.002	8.69	2.335	3.544	12.673
Learning attitude	Unassuming equal variance			3.524	97.26	0.002	8.69	2.335	3.544	12.673
Accounting	Assumed equal variance	17.715	0	2.987	98	0.003	6.68	1.987	1.956	9.624
Accounting	Unassuming equal variance			2.987	94.35	0.003	6.68	1.987	1.948	9.657

Combining the results of the above two tables, it can be seen that in terms of learning attitude, the average score of the experimental group is 8.69 points higher than that of the control group, while the results of the t-test show that the significance (two-tailed) value is 0.01 less than 0.05, and the 95% confidence interval of the difference does not include 0, which indicates that the difference between the two groups is obvious. In terms of accounting literacy, the mean score of the experimental group was 6.68 points higher than that of the control group, while the results of the t-test showed that the significance (two-tailed) value was 0.04 less than 0.05, and the difference 95% confidence interval did not include 0, which again indicated a significant difference between the two groups.

In summary, after one semester of study, the experimental group performed significantly better than the control group in both learning attitude and accounting literacy.

Then paired sample t-tests were conducted for within-group learning attitude and accounting literacy pre-test and post-test data. 1)

Paired-sample t-test for control group pre-test and post-test data

Table 7 shows the paired-sample t-test for the control group’s pretest and posttest data, and Table 8 shows the results of the paired-sample t-test for the control group’s learning attitude and accounting literacy pretest and posttest.

From Table 7, it can be concluded that the mean scores of both learning attitude and accounting literacy posttest of the control group have increased compared with the pre-test, and from Table 8, it can be seen that the demonstrative (two-tailed) value of pair 1 (learning attitude) is 0.009 less than 0.05, while the 95% confidence interval of the difference excludes 0, i.e., the difference of pair 1 is significant; the demonstrative (two-tailed) value of pair 2 (accounting literacy) is 0.402 greater than 0.05, the The simultaneous difference 95% confidence interval includes 0, i.e., the difference in pair 2 is not significant. In conclusion, after one semester of learning in the blended teaching mode, the students in the control group made significant progress in learning attitude and insignificant progress in accounting literacy.

2)

Paired-samples t-test for pre-test and post-test data of the experimental group

Table 9 shows the paired samples t-test for the pre-test and post-test data of the control group, and Table 10 shows the results of the paired samples t-test for the pre-test and post-test of learning attitude and accounting literacy of the control group.

From Table 9, it can be concluded that the mean scores of both learning attitude and accounting literacy post-test of the experimental group are significantly higher than the pre-test, and from Table 10, it can be seen that the display (two-tailed) value of pair 1 (learning attitude) is 0.000 less than 0.05, while the 95% confidence interval of the difference does not include 0, that is to say, the difference of pair 1 is obvious; the display (two-tailed) value of pair 2 (accounting literacy) is 0.021 less than 0.05, while the 95% confidence interval of the difference does not include 0, i.e., the difference of pairing 2 is significant. In summary, after a semester of study, the students in the experimental group had a significant improvement in both their learning attitude and accounting literacy.

In conclusion, after one semester of practicing the blended teaching mode, the students in the experimental group showed a significant improvement in their grades in the final exam compared with the control group, and there was a significant improvement in their learning attitude and accounting literacy.

Table 7.

Control group matching sample statistics

		Mean	N	SD	Standard error mean
Learning attitude	Pretest	48.26	50	3.401	0.322
Learning attitude	Posttest	49.15	50	2.827	0.746
Accounting	Pretest	33.87	50	3.522	0.309
Accounting	Posttest	34.28	50	2.555	0.376

Table 8.

Control group matching sample t test results

		Mean	SD	Standard error mean	95% confidence interval		t	df	Sig. (Double)
		Mean	SD	Standard error mean	Down	Up	t	df	Sig. (Double)
Learning attitude	Pretest	-5.426	12.935	1.999	-9.451	-1.408	-2.735	49	0.008
Learning attitude	Posttest	-5.426	12.935	1.999	-9.451	-1.408	-2.735	49	0.008
Accounting	Pretest	-1.145	8.759	1.36	-3.864	1.587	-0.856	49	0.405
Accounting	Posttest	-1.145	8.759	1.36	-3.864	1.587	-0.856	49	0.405

Table 9.

The results of the experimental group were paired with the sample

		Mean	N	SD	Standard error mean
Learning attitude	Pretest	44.83	50	4.252	0.966
Learning attitude	Posttest	57.84	50	4.514	0.674
Accounting	Pretest	38.27	50	4.75	0.38
Accounting	Posttest	40.96	50	2.907	0.698

Table 10.

Test results of the mating sample of the experimental group

		Mean	SD	Standard error mean	95% confidence interval		t	df	Sig. (Double)
		Mean	SD	Standard error mean	Down	Up	t	df	Sig. (Double)
Learning attitude	Pretest	-12.482	13.286	2.056	-16.375	-8.359	-6.156	49	0
Learning attitude	Posttest	-12.482	13.286	2.056	-16.375	-8.359	-6.156	49	0
Accounting	Pretest	-5.518	14.937	2.315	-10.183	-0.881	-2.396	49	0.023
Accounting	Posttest	-5.518	14.937	2.315	-10.183	-0.881	-2.396	49	0.023

4

Conclusion

In this paper, based on the principle of constructivism, a blended teaching model for accounting majors is designed that consists of independent learning before class, discussion and exchange during class, and consolidation and enhancement after class. The lag sequence analysis method was used to analyze the behavioral sequences of teacher-student interactions, and teaching experiments were carried out in two classes selected to major in accounting at a university. In the lag sequence analysis, it was found that in addition to the 15 significant behavioral sequences pointing to themselves, there are 13 other significant behavioral sequences, which together reflect the laws and characteristics of teacher-student interaction behavior. By analyzing these significant behavior sequences, it can help teachers reflect on classroom teaching and promote their professional development. At the end of the semester posttest whether it is the theory test, practical test or total score, the experimental group is higher than the control group, of which the practical score experimental group is 4.65 points higher than the control group. Comprehensively, the teaching quality of the experimental group using the blended teaching mode of this paper is significantly improved compared with the pre-test and is also better than the control group.

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A Study of the Effectiveness of Blended Teaching Models for Accounting Majors

Fujiao Hu

Zhijun Li

Publié en ligne: 19 mars 2025

Reçu: 05 nov. 2024

Accepté: 14 févr. 2025

DOI: https://doi.org/10.2478/amns-2025-0466

Mots clésConstructivism, Lagged behavioral sequences, Paired samples t-test, Blended instruction

© 2025 Fujiao Hu et al., published by Sciendo

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

Mots clés
Constructivism, Lagged behavioral sequences, Paired samples t-test, Blended instruction

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