Analyzing the Differences of Interaction and Engagement in a Smart Classroom and a Traditional Classroom

Abstract

Interaction in the classroom plays the key role for cultivating students’ 21st century skills. Insufficient breadth of interaction, uneven interaction opportunities, and chaotic interaction existed in many classrooms. With the integration of technology into education, many smart classrooms were built, with one of the aims being to promote interaction. However, the differences of interaction behaviors and engagement in a smart class versus a traditional class could rarely be found in literature, especially with the same teacher lecturing in both classes. In this study, a quasi-experiment was conducted by one experienced English teacher lecturing in a smart classroom with students and a traditional classroom with students for one semester. Research data were obtained by coding the 8 class videos with the proposed “Classroom Interaction Analysis Framework” and the adapted engagement questionnaire, and the data were analyzed using SPSS 24. Results showed that there were no significant differences in either interpersonal interaction or human–technology interaction; however students experienced significantly more engagement in the smart classroom. The reasons were analyzed and interaction patterns in smart classroom were discussed. Finally, a smart classroom interaction model was proposed to promote classroom interaction by considering the interplay of pedagogy, space, and technology.

1. Introduction

One of the key roles claimed for information and communication technology (ICT) in promoting learning is interactivity, i.e., the ability to respond contingently to the learner’s actions [1,2]. With the development of ICT, more social, interactive, flexible, and student-centered learning environments are realized [3]. The smart classroom is a kind of typical intelligent learning environment [4,5,6], with the aims to increase teachers’ interaction opportunities and overcome teachers’ attitudinal barriers to technology [7,8,9].

A smart classroom is defined as a physical classroom that is enriched with digital, context-aware, and adaptive devices [4,10,11]. Integrating the advanced forms of educational technology, a smart classroom increases the instructors’ ability to facilitate students’ learning [3,12] and provide the necessary conditions for the training of students’ 21st century skills [13,14].

The continuous infiltration and integration of technology in classroom environments provides an opportunity to enhance interpersonal interaction in the classroom [1,15]. Technically configured smart classrooms may enhance the diversity and effectiveness of classroom interactions [16,17,18], but few studies could be found analyzing the differences of interaction in smart classrooms versus traditional classrooms.

2. Research Status of Classroom Interaction

Many studies have shown that classroom interaction can affect the classroom atmosphere, students’ behavior, and the level of engagement, and thus the quality of classroom teaching [19,20].

However, in the traditional classroom, some inherent problems seriously restricted the overall quality of interpersonal interaction in the classroom [21], for example, fixed seating, rigid multi-media console, and lack of student’s presenting screen. Umida et al. [22] pointed out that the interaction between teachers and students was chaotic and students were in a passive position in the traditional classroom. Suping et al. [23] proposed that interaction in traditional classroom generally characterized by massive teacher–student interaction, lack of emotional interaction, insufficient interaction, and normally one-way interaction of “one-way obedience”. In the traditional classroom environment, most teachers played the role of “indoctrination”, where students passively received knowledge. Teachers and students interacted only with words at a shallow level around knowledge in the textbook, and there was little communication between students, which was not conducive to the development of students’ 21st century skills.

In regard to technology-enhanced interaction in the classroom, many studies have been conducted to evaluate the effectiveness of using specific tools or systems for classroom interaction. Mimouni (2022) [24] reported the findings of using clickers for interaction, and it was found that students were more engaged in learning, group interaction was improved, and the pedagogy changed from teacher-centered to student-centered. Sun and Hsiu (2022) [25] also found that the classroom response system could facilitate interaction among learners and content, enhance students’ engagement with entrepreneurial knowledge acquisition, and improve students’ motivation. Wang et al. (2022) [26] conducted research in the smart classroom to investigate the association of the layout of smart classroom and real-time social interactions.

For interaction patterns in a technology-rich environment, Chen et al. (2011) [27] mentioned that except for interpersonal interaction, classroom interaction should also include human–technology interaction, human–resource interaction, human–environment interaction, technology–technology interaction, technology–resource interaction, environment–resource interaction, and resource–resource interaction. Martin, Parker, and Deale (2012) [28] examined the interactivity in a synchronous virtual classroom and found that interactions were promoted by the live communication that occurred in the virtual classroom. The four types of interaction of learner–teacher, learner–learner, learner–interface and learner–content were identified in the paper. Yang et al. (2019) [29] investigated the interaction in a blended synchronous cyber classroom and classified the interaction pattern of teacher using technology, student using technology, teacher talking, and students talking. Wang et al. (2015) [30] proposed an interaction observation tool for the smart classroom, including interaction subjects, contents of interaction, degree of technology support, degree of interaction, degree of feedback, and degree of engagement.

Pedagogical issues on using technology to enhance interactivity have gradually attracted researchers’ attention. He et al. (2017) [31] argued that the flexible space and interactive devices, intelligent tools, and rich-media information in smart classrooms could provide new opportunities for group collaboration learning. Persaud and Persaud (2019) [32] investigated the effectiveness of using a web-based Student Response System to promote interaction combined with the Think-Pair-Share model. Lucas et al. (2021) [33] studied the value of online interaction and they found that instructor feedback on participation, instructor interactivity, and asynchronous interaction in discussion forums were the three significant values for online interaction. At present, many schools have built smart classrooms, but in the process of teaching practice, the role of technology in supporting classroom interaction remains to be explored. Therefore, the research questions of this paper are: (1) what are the differences of interaction in a smart classroom and interaction in the traditional classroom if teaching is conducted by the same teacher? (2) Does teaching in a smart classroom promote students’ engagement?

3. Method

3.1. Participants

A total of 106 students were selected from two parallel classes of the first-year undergraduate cohort of a vocational college in Zhejiang province, China. There were 54 students in the experimental smart class and 52 students in the control traditional class. The average of English scores (93.035, 92.900) and standard deviation (11.698, 11.675) of the experimental and control classes are close. Both classes use the same teaching materials and are taught by the same English teacher. The teacher has been teaching for many years, has rich teaching experience, and has a great interest in the reform of the teaching model under the technical support.

In the tradition classroom used in this study, a whiteboard and a blackboard were equipped to allow teachers to project their slides or contents from the Internet onto the screen, while the smart classroom was equipped with Wi-Fi, one interactive whiteboard, one blackboard, one tablet for every student, and an interactive teaching platform as shown in Figure 1. In the smart classroom environment, teachers and students carry out various teaching activities based on mobile phone terminals, teachers mainly use cloud classes, micro teaching assistants and other teaching apps to set up classroom exercises and discussion activities, students with the technology-enhanced self-study, search resources, interactive discussion, students’ results, and exercises can be presented instantly with the help of a projector. Teachers and students in the control group were taught in traditional multimedia classrooms.

3.2. Data Collection Tools

The study lasted one semester with the teacher teaching in both a smart classroom and a traditional classroom for 8 classes. At the end of the experiment, the two kinds of data were collected: (1) the 4 class videos from the smart classroom and 4 class videos from the traditional classroom were analyzed by using “Classroom Interaction Analysis Framework”, (2) 37 questionnaires from smart classroom and 44 from traditional classroom were collected by using “Engagement Questionnaire”. The experiment design is show in

Table 1. The quasi-experiment design.

Group	Teacher	Experiment Treatment	Data Collection
Experiment group (n = 54)	Teacher A	(1) Smart classroom (2) Technology-enhanced teaching	(1) Interaction behavior coding (2) Engagement questionnaire
Control group (n = 52)	Teacher A	(1) Traditional classroom (2) Teaching in traditional way	(1) Interaction behavior coding (2) Engagement questionnaire

.

In order to analyzing the video, the Classroom Interaction Analysis Framework was developed according to the literature and our previous research [32,34].

Interests in research on interaction in the classroom has a long history. Smith (1961) [35] pioneered classroom interaction research through the classification of verbal interaction behavior and the mutual interaction of the teachers and pupils. There are two major prerequisites for effective classroom interaction analysis: (1) the structure of classroom interaction; (2) the classification of teacher and pupil interaction behaviors.

A classroom observation method is often adopted for analyzing the teaching and learning behavior in a classroom. The Flanders Interactive Analysis System (FIAS) was the widely used behavior coding method for teacher and student activities, which includes teacher-led and pupil-led teacher talk and pupil talk [36]. According to the interaction analysis coding system proposed by Zhang et al. [37], Ye et al. [38], and Jeber et al. (2021) [39], both human and technology should be considered in technology-rich classrooms. Therefore, the coding system of this study includes two kinds of interaction of “interpersonal interaction” and “human–tech interaction”, as shown in

Table 2. Classroom Interaction Analysis Framework.

Dimension	Activity		Coding
Interpersonal interaction	Teacher–student	Teacher talk	Accepting student’s emotion	TS1
			Encouraging or praising students	TS2
			Accepting student’s idea	TS3
			Asking questions	TS4
			Lecturing	TS5
			Guiding	TS6
			Criticizing or maintaining authority	TS7
		Student talk	Passively answering questions	ST8
			Actively answering questions	ST9
			Asking questions	ST10
	Student–student		Working with peers	SS11
Human–tech interaction	Teacher–tool		Using slides	TM12
			Projecting content to whiteboard	TM13
			Blackboard writing	TM14
			Sending exercises	TM15
			Tech instruction	TM16
			Viewing statistics	TM17
			Reductant operation	SM18
	Student–tool		Viewing the textbook	SM19
			Writing on paper	SM20
			Writing on tablet	SM21
			Tech support assessment	SM22
			Presentation	SM23
			Collaborative practice	SM24
			Scan QR code	SM25

.

The “engagement questionnaire” consisted of 6 items, with 3 for behavioral engagement and 3 for emotional engagement adapted from Ellen Skinner et al. (2008) [40]. The Cronbach Alpha was 0.853, indicating that the reliability of the questionnaire was acceptable.

3.3. The Coding Process

Before formally coding the course video, in order to enable the coder to correctly understand the indicators of the coding tool and the smooth use of the coding tool to encode the classroom video, to ensure the accuracy of video coding, two coders were trained first. In the process of encoding the classroom video, two coders encoded the same classroom video, and if there was a disagreement, the researcher and the coder analyzed together to form a video encoding. Due to the complexity and overlap of the teaching interaction behavior, the following coding rules were agreed upon in this study: (1) The frequency of teacher–student dialogue in English classroom is faster, so take a sample every 1 s, give a coding symbol, and record this behavior; (2) when a variety of interactive behaviors occur in unit time, choose the interaction behavior which is different from the previous unit time; (3) when students carry out inquiry and discussion activities, the teacher tours and does not guide or organize the group, then only record the students to explore and discuss; (4) when there is a classroom pause in teaching due to improper use of technology or technical failure, record edgy operation as “redundant operation”.

According to the classroom behavior coding table based on the interaction analysis of the smart classroom, the statistics of teacher–student interaction after coding are shown

Table 3. Behavior coding statistics sample.

No.	Time Begins	Time Lasts (s)	Coding Behavior	Notes
1	0:01:05	20	TS2	Encouraging or praising students
2	0:01:25	30	TS4	Teacher answering questions
3	0:01:55	35	TS6	Teacher guiding student’s thinking

.

3.4. Ethics Statement

The study was approved by the Ethics Committee of the School of Education in Hangzhou Normal University (China). The teachers and students involved in the study agreed to participate voluntarily with informed consent. The data collected from the classroom video analysis was confidential without any potential risk to the integrity of the subjects.

4. Results

4.1. Interpersonal Interaction

The results of the means and independent samples t-tests for student–teacher and student–student behaviors (shown in

Table 4. Comparison of interpersonal interaction.

Dimension	Experimental Group (n = 4)	Control Group (n = 4)	Independent-Samples t-Test
	Mean	Mean	t	Sig.(two-tailed)
Teacher–student	285.75	379.75	2.244	0.066
Student–student	4.25	0.25	3.021	0.416

) showed that there were no significant differences (p > 0.05) in the interaction behaviors of teachers–students and students–students between the smart classroom and the traditional classroom. Although there was no significant difference, the mean value of teacher–student interaction behaviors in the traditional classroom was higher than that in the smart classroom, while the mean value of student–student interaction behaviors in the former was lower than that in the latter. This indicated that the traditional subjectivity of the teacher is weakened and the subjectivity of the students is improved in the smart classroom.

To further clarify the ways that interpersonal interaction behavioral changed, the following analyses were conducted for each item of teacher–student and student–student interaction behaviors. The results of independent sample t-tests (as in

Table 5. Comparison of teacher–student interaction.

Dimension	Item	Experimental Group (n = 4)	Control Group (n = 4)	Independent-Samples t-Test
		Mean	Mean	t	Sig.(two-tailed)
Teacher–student	Accepting student’s emotion	3.50	2.75	0.655	0.537
	Encouraging or praising students	9.25	4.75	1.748	0.131
	Accepting student’s idea	12.75	12.25	0.170	0.870
	Asking questions	59.75	66.25	0.382	0.724
	Lecturing	177.25	278.50	2.625	0.062
	Guiding	22.75	14.50	1.964	0.120
	Criticizing or Maintaining authority	0.5	0.75	0.447	0.670

) for each sub-item of teacher–student interaction behavior in the experimental and control groups showed no significant differences (p > 0.05) for all items. The experimental group had higher means than the control group for the items of accepting students’ emotions, encouraging or praising students, accepting students’ ideas, and lecturing; the experimental class had lower means than the control class for the sub-items of asking questions, lecturing, and criticizing or maintaining authority. The analysis of teacher–student interaction behavior showed that the effective interaction between teachers and students was enhanced in the smart classroom, and students and teachers were able to interact more positively with each other and the classroom atmosphere was more harmonious. A review of the classroom recordings revealed that in the smart classroom, teachers used encouraging language to talk to students as equals. For example, when students use their cell phones to answer questions online, teachers provide real-time updates on their answers and give feedback to students who have done well, such as “XXX has finished” and “XXX has done well, all correct”. The use of electronic devices such as cell phones provides more opportunities and methods for teachers to quickly grasp students’ learning and provide timely and effective guidance, facilitating individualized and differentiated communication between teachers and students, and creating an atmosphere of equal and harmonious interaction between teachers and students in the classroom.

The student–student interaction behavior, i.e., the item of working with peers, has shown no significant differences between experiment group and control group. Since this experimental course was a college English listening course, listening exercises were predominant in the class and there are fewer opportunities for discussion, which caused the differences between interaction in the smart classroom and traditional classroom to be poorly represented, as shown in

Table 6. Comparison of student–student interaction.

Dimension	Item	Experimental Group (n = 4)	Control Group (n = 4)
		Mean	Mean	t
student–student	Working with peers	4.25	0.25	0.655

.

4.2. Human–Tech Interaction

The major difference between the smart classroom and the traditional classroom is the use of technology. To further analyze the changes in human–tech interactions, the interaction behaviors of teachers–tool and students–tool in the classroom were statistically and analytically analyzed. The results of independent sample t-tests of teacher–tool and student–tool interaction behaviors within the smart and traditional classrooms (shown in

Table 7. Comparison of human–tech interaction.

Dimension	Experimental Group (n = 4)	Control Group (n = 4)	Independent-Samples t-Test
	Mean	Mean	t	Mean
Teacher–tool	32.25	14.50	2.919 *	0.027
Student–tool	292.75	230.00	1.251	0.269

* p < 0.05.

) revealed that there was a significant difference in teacher–tool interaction behaviors between the two types of classrooms (t = 2.919, p < 0.05), with a significant increase in teacher–tool interaction behaviors in the smart classroom environment. Although there was no significant difference in student–tool interaction behaviors between the two types of classrooms, the mean value of student–tool interaction behaviors was higher in the smart classroom than in the traditional classroom. It can be concluded that teaching in the smart classroom environment increases the interaction between people and technology, where the number of interactive behaviors between teachers and tools is significantly higher, which indicates that the smart classroom places higher demands on teachers’ ability to apply technology.

To explore the differences more deeply, further analysis of the specific items for teacher–tool and student–tool follows (as shown in

Table 8. Comparison of teacher–tool interaction.

Dimension	Item	Experimental Group (n = 4)	Control Group (n = 4)	Independent-Samples t-Test
		Mean	Mean	t	Mean
Teacher–tool	Using slides	14.00	13.75	0.048	0.963
	Projecting content to white board	1.00	0.00	1.732	0.134
	Sending exercises	2.25	0.00	2.029	0.135
	Tech instruction	4.50	0.00	2.141	0.122
	Viewing statistics	7.75	0.00	2.758	0.070
	Reductant operation	2.75	0.75	1.372	0.219

). There were no significant differences in any of the sub-items of teacher–tool interaction behaviors. The sub-item of using slides in the smart classroom and in the traditional classroom was the most frequent of the teacher–tool interaction behaviors, and the mean of this behavior was comparable in both types of classrooms.

The teaching behaviors of projecting content to whiteboard, sending exercises, tech instruction, and viewing statistics were only available in the smart classroom environment, and the highest frequency was for the item of viewing statistics. Accordingly, the following conclusions can be drawn: teaching in the smart classroom increased teacher–tool interaction but the dominant interaction behavior is still using slides and teachers tend to use the function of response statistics most in the smart classroom environment to obtain students’ learning situation in real time.

In both the experimental and control groups, teachers used the tools in a redundant manner, and the mean value was higher in the experimental group than in the control group. This indicates that teachers in the smart classroom environment are more likely to make technical errors, which further suggests that teaching in the smart classroom environment places new and higher-level technical requirements on teachers.

The results of the independent sample t-test for the student–tool dimension showed (as shown in

Table 9. Comparison of Student–tool interaction.

Dimension	Item	Experimental Group (n = 4)	Control Group (n = 4)	Independent-Samples t-Test
		Mean	Mean	t	Mean
Student–tool	Viewing the textbook	18.75	4.75	2.965 *	0.025
	Writing on paper	169.75	225.25	−1.164	0.305
	Writing on pad	92.75	0	3.318 *	0.045
	Tech support assessment	1.25	0	1.667	0.194
	Presentation	0.25	0	1.000	0.391
	Scan QR code	10	0	1.508	0.229

* p < 0.05.

) that there was a significant difference between viewing the textbook (t = 2.965, p = 0.025) and writing on iPad (t = 3.318, p = 0.045) in the experimental and control groups. This indicates that the interaction between students and mobile devices such as cell phones significantly increased in the smart classroom environment, and more writing was switched to the electronic screen.

In the paper writing item, the mean value of the experimental group was lower than that of the control group. Combined with the analysis of the writing on iPad items in the previous paragraph, it can be concluded that in the smart classroom environment, students no longer used only paper writing, but increased the cell phone writing as a way to answer.

Comparing the two classroom environments, there were no significant differences between the three sub-items of technology-supported evaluation, presentation, and scan QR code, and the means of all these interactive behaviors were relatively low in smart classroom.

4.3. Students’ Engagement

The results of the independent sample t-test of the students’ affective engagement dimension (as shown in

Table 10. Comparison of emotion engagement.

Dimension	Item	Experimental Group (n = 37)	Control Group (n = 44)	Independent-Samples t-Test
		Mean	Mean	t	Mean
Affective engagement	Do you enjoy the process of group discussion?	3.41	3.05	1.839	0.070
	Do you enjoy the process of teaching English listening and speaking classes?	3.46	3.02	2.323 *	0.023
	Are you looking forward to continuing to study English listening and speaking at university?	3.54	2.95	2.844 **	0.006

* p < 0.05, ** p < 0.01.

) showed that there was a significant difference between the experimental group and the control group in term of “Do you enjoy the process of teaching English listening and speaking classes?” (t = 2.323, p < 0.05) and “Are you looking forward to continuing to study English listening and speaking at university?” (t = 2.844, p < 0.01). There was no significant difference between the experimental and control groups on the item of “Do you enjoy the process of group discussion?”. This indicates that teaching in the smart classroom increases students’ enjoyment of the English classroom, but at the same time, there is little motivation for group discussion and little emotional involvement in this area. This further confirms that the teacher–student interactions in the smart classroom environment were more adequate and cordial in the video analysis, and also reflects the inadequate and ineffective student–student interactions.

The results of the independent sample t-test on the dimension of students’ behavioral engagement (as shown in

Table 11. Comparison of behavior engagement.

Dimension	Item	Experimental Group (n = 37)	Control Group (n = 44)	Independent-Saples t-Test
		Mean	Mean	t	Mean
Behavior engagement	Do you actively answer the teaching questions in each class?	2.97	2.48	2.448 *	0.017
	Do you actively participate in cooperative learning in English classes?	3.62	3.18	2.609 *	0.011
	Do you work hard to solve the problems encountered in the discussion during English listening and speaking classes?	3.46	2.95	2.815 **	0.006

* p < 0.05, ** p < 0.01.

) showed that, compared with the control group, there was a significant difference in all three items. This shows that students’ behavioral engagement is higher in the smart classroom, especially in the problem discussion, than in the traditional classroom.

5. Discussion

5.1. Interaction Behaviors in a Smart Classroom

Classroom interaction in a smart classroom includes interpersonal and human–tech interaction. Interpersonal interaction is mainly the interaction between teacher and one student, teachers’ interaction with a group of students, teachers’ interaction with all students, and students’ interaction with other students. Human–tech interaction is mainly used to support teacher’s presentation, management, real-time interaction, and feedback. Interpersonal interaction and human–tech interaction interact with each other, mainly relying on teachers’ design of learning activities. It is the pedagogy that matters, not the technology, which could also explain why there were no significant differences. For teaching in a smart classroom, it is important to consider the two kinds of interactions and integrate technology into pedagogy.

As shown in

Table 12. The main contents of interactions in a smart classroom.

Interaction Types	Categories	Contents
Interpersonal interaction	Teacher to one student	Ask and answer questions, guiding, oral evaluation, etc.
	Teacher to group students	Organize and guide, ask and answer questions, oral evaluation, etc.
	Teacher to whole class	Organization and management, explanation and demonstration, ask and answer questions, guide the inspired, etc.
	Student–student interaction	Discussion and communication, speaking and sharing, mutual evaluation, etc.
Human–technology interaction	Content presentation	Blackboard, interactive whiteboards, flat panel rendering and projecting, etc.
	Resource accessing	Recorded broadcast, teacher access resources, student access resources, etc.
	Environment managing	Manage and control the hardware and software in the classroom
	Real-time feedback	Upload and distribute, practice and testing, give a like, vies to answer first, etc.
	Learning outcome analytics	Statistical analysis of data, data mining and learning analysis, etc.

, for human–tech interaction, teachers could utilize these technologies to support presentation, accessing learning resources, managing class environment, giving students’ real-time feedback, and analyzing learning outcome. Teachers could consider these pedagogy interactions supported by technology in the smart classroom. For interpersonal interaction, the interaction with a student, a group of students, the whole class, and student–student interaction should be considered. It should be noticed that these two kinds of interactions are always interrelated with each other, which should also be considered in the designing process.

5.2. Interaction Model for a Smart Classroom

In a smart classroom full of technology, a teacher’s ICT skills should be improved to conduct technology-enhanced pedagogy to promote interaction in the classroom. Based on theoretical analysis and practical insights, the interaction model for a smart classroom was proposed, as shown in Figure 2. First, refer to the PST (Pedagogy-Space-Technology) framework proposed by David Radcliffe (2008) [41]; this model consisted of the three dimensions of pedagogy, classroom space, and information technology. “Space” mainly refers to the physical environment in a classroom, including the division of classroom areas, the layout of desks and chairs, as well as sound, light, temperature, and other related equipment. Huang et al. (2012) [5] proposed the “SMART” classroom concept model with the five dimensions of “Showing”, “Managing”, “Accessing”, “Real-time feedback”, and “Testing”. Accordingly, as shown in Figure 2, technologies facilitating teachers’ content presentation, management of classroom climate, assessing learning resources, providing students real-time feedback, and learning analytics should be considered for using a smart classroom.

In order to effectively carry out classroom interaction, pedagogy should be integrated with both space and technology, by considering the five dimensions of smart classroom environment. Dong et al. (2018) [42] argued that innovative teaching comprises of teaching methods, media, learning content, evaluation, learning objectives, management, and many other factors. According to Voss et al. (2011) [43], “general pedagogic knowledge” consisted of five dimensions: knowledge of classroom management, knowledge of teaching methods, knowledge of classroom evaluation, knowledge of learning process, and knowledge of individual learner characteristics. Therefore, to enhance classroom interaction, from a pedagogy perspective, the five aspects of “objectives”, “content”, “methods”, “management”, and “evaluation” were included in the model.

The aspects of pedagogy should be considered when designing classroom interaction, and also the smart classroom combined both space and technology providing environmental support for classroom interaction from the five dimensions. Therefore, designing interaction in a smart classroom could consider the pedagogy aspects and the supports of smart environments from the aspects of presentation of teaching/learning content, management of class climate, accessing learning resources, providing real-time feedback, and analyzing learning outcome.

6. Limitations and Conclusions

This study investigated the differences of interaction and engagement in a smart classroom and the traditional classroom by using a behavior coding method on 8 lecture videos in the two kinds of classrooms. The results showed that no significant differences were found in either interpersonal interaction or human–tech interactions; however, students experienced more engagement in a smart classroom. Based on the results, interaction patterns and an interaction model in a smart classroom are proposed for promoting interaction by integrating technology, pedagogy, and space.

This study was only a pilot study on classroom interaction, the sample could be enlarged and a sophisticated data analysis method could be adopted. In the future, the comparative study on the interaction between the smart classroom and the traditional classroom can be further deepened from the aspects of theory, design, and practice.

Firstly, in terms of theoretical research, the technology-enhanced interaction patterns and the interplay between interpersonal interaction and human–tech interaction should be explored further. In addition, the model proposed in this study to promote interaction in smart classrooms could be further refined in large-scale smart classroom practices. Secondly, in terms of design research, it is necessary to design a more reasonable interaction analysis model under the guidance of theory and combining with the latest literature interaction research. Thirdly, in terms of practical research, a long-term and evidence-based experiment will be conducted to investigate how to improve ICT competency of teachers, the relationship between interaction and performance, and the auto-interaction behavior coding methods in smart classroom.