Journal of Computer Assisted Learning

2.1 CSCL and OCL: Collaborative learning in a computerized environment

A collaborative learning mechanism underpins many technological systems used in pedagogic institutions. The terms CSCL and OCL relate to the field of research that discusses CSCL. Recently developed models have tried to identify collaboration types in various systems of this sort (Rodríguez‐Triana, Martínez‐Monés, Asensio‐Pérez, & Dimitriadis, 2015; Roschelle et al., 2011). Additionally, empirical evaluation tools have been developed to facilitate comprehension and evaluation of the extent of students' readiness for collaborative learning experiences in the digital environment—a concept known as students' readiness for CSCL. Among other things, research has studied motivation for collaborative learning, potential behaviours involved in collaborative learning and online learning skills (Xiong, Hyo‐Jeong, & Toh, 2015). An important characteristic of the assimilation of CSCL relates to the fact that students are more amenable than lecturers to the integration of collaborative technologies in learning (Roblyer, Daniel, Webb, Herman, & Witty, 2010).

According to Jang (2014), qualitative research is a central tool in research examining the use of collaborative technologies in higher education and their influence on the students' learning experience and achievements. Jang investigated how collaborative learning activities contribute to the creation of new knowledge through the application of prior knowledge. Jang indicated that there was a strong correlation between the students' learning performances and their perception of the influence of use of collaborative technologies on their learning experience.

Previous studies found that online collaboration in learning is not limited to communication and sharing of knowledge (Romero & Lambropoulos, 2011), rather it involves the shared construction of ideas and problem‐solving in an online environment (Inayat, ul Amin, Inayat, & Salim, 2013). Studies have investigated the influence of collaborative online learning on learners' cognitive abilities and also on their social and psychological functioning (Kirschner, Kreijns, Phielix, & Fransen, 2015). Inter alia, research has considered how collaborative performance enables learners to increase satisfaction and trust in the studied knowledge (Son et al., 2012). Social–emotional aspects of community activities have also been discussed, and their contribution to assignment effectiveness has been assessed on the individual and group levels (Jeong & Hmelo‐Silver, 2016; Remesal & Colomina, 2013; Xu, Du, & Fan, 2015). In the psychological dimension, it has been proven that collaboration out of extrinsic motivation may alter CSCL habits and lead to the development of cooperation out of intrinsic motivation (Fischer, Kollar, Stegmann, & Wecker, 2013). Different studies investigated the influence of CSCL on learning outcomes. However, no consensus has been reached concerning the definition of high‐order collaborative learning in this context (Luhrs & McAnally‐Salas, 2016).

2.2 LCT: Technologies for the recording of lectures in teaching

When applying LCT in teaching, cameras are integrated in lectures at different levels: photographing the board, audio recording, video recording, and so forth. There are two reasons for the increase in LCT systems' use in higher education institutions in recent years: dizzying technological advances and the students' digital skills (Newton, Tucker, Dawson, & Currie, 2014).

Sloan and Lewis (2014) distinguish four research categories in the LCT field:

1. Types of use—relates to the manners in which these tools are used (Zhu & Bergom, 2010) as appropriate for the different disciplines (DeSantis, Pantalone, & Wiseman, 2010; Smith & Suzuki, 2015) in order to advance learning (Smith & Sodano, 2011).
2. Influence on students' attendance—this category was discussed widely by Karnad (2013). It relates to studies on the influence of LCT use on students' attendance at lectures and their involvement in their studies. The fear that the use of cameras to record lectures would reduce students' attendance in courses was disproved in some of the studies (Nashash & Gunn, 2013; Toppin, 2011). Studies investigating students' viewpoints on the use of LCT found that this strategy had an influence on their motivation to learn; however, this was not expressed in the learning results (Pale, Petrovic, & Jeren, 2014). Similarly, a study of the Tegrity system that is very similar in characteristics to the ClassBoost system found that students' viewing of the recorded lectures had no influence on their final grades (Bollmeier, Wenger, & Forinash, 2010). Nevertheless, Drouin (2014) found that use of lecture recording led to a decrease in percentage of attendance and also in the learners' achievements at the end of the course. Drouin compared students who had studied in a course where they had access to LCT resources and students who studied a course without access to recordings. Additional analysis that he conducted indicated a decrease in the students' active involvement during the lecture in a course that included the use of LCT.
3. Students' learning styles—this research relates to students' different learning styles in the LCT field. These research findings identify diverse learning and performance styles in the use of LCT (McCunn & Newton, 2015; Yu, Wang, & Su, 2015). However, there is a clear need for additional studies in this field. One of the distinctions noted in the context of LCT use was between deep and superficial learning styles. It was concluded that students who have a deep learning style tend to be assisted by the lecture recordings on a regular basis and to attain higher achievements (Vajoczki, Watt, Marquis, Vine, & Liao, 2011). Additionally, a gap was observed in the frequency and effectiveness of use of LCT between students with a high‐average grade and students with a low‐average grade. The first group watched the recordings at a lower frequency, and they did not watch the entire recording, only parts of it (Owston, Lupshenyuk, & Wideman, 2011). Preston et al. (2010) discovered that the use of LCT is more effective in larger classes than in smaller classes and less effective in populations with high rates of interaction. This finding is very important for the present study because of its focus on the collaborative dimension.
4. Objective measures of learning—these studies examine to what extent the use of LCT correlates with objective measures of learning. Inter alia the students' performances and level of satisfaction were measured (Euzent, Martin, Moskal, & Moskal, 2011; Ford, Burns, Mitch, & Gomez, 2012). This category also includes studies focusing on the students' achievements. The influence of LCT on measures of learning was also examined with regard to aspects involved in improving access to higher education for populations with special needs (Watt et al., 2014). In this context, it is important to note the contribution of models which formed objective measurement tools to evaluate the influence of use of LCT (von Konsky, Ivins, & Gribble, 2009).

The different directions of the above‐mentioned studies and widespread spectrum of findings may be due to differences between the different studied disciplines, the types of use of the system, different teaching styles, and student characteristics. The present study was prompted by the fact that until now, as far as could be ascertained, there has been no study on the influence of LCT on CSCL. Also, there has been no study examining these different issues among student teachers, in a college that trains them for work as teachers in the education system in the digital era.

This study aims to provide an example of usage habits and characteristics of collaborative learning at the inception of a process to integrate innovative technology in college teaching. The process took place in an academic college that trains teachers for the education system, and the research examined the student teachers' viewpoints on this process.

2.3 An innovative pedagogical framework in teacher education

Many questions are asked today on how to train teachers to successfully assimilate technology at school (for example, Haydn, 2014; Levin & Tsybulsky, 2017). Thus, one of the functions of contemporary teacher training is to prepare teachers for an education system that uses technology and enable teachers to educate for 21st century skills, including collaborative learning patterns, skills, and learning practices (Sadaf, Newby, & Ertmer, 2016; Tondeur, van Braak, Siddiq, & Scherer, 2016). Thus, for example, on the grounds of his experience as a CALL teacher trainer, Simone Torsani suggested a twofold route to the preparation of teachers for the integration of technology in teaching.

… an in‐depth study of the traditional language‐teaching and technology connection serves, indeed, as a premise for the usage and integration of computer‐assisted materials and procedures. (Torsani, 2016, p. 6).

This example relates to the need for rethinking of traditional language teaching in preparation for the inclusion of technology in language teaching, something that is certainly also relevant for the teaching of other disciplines in teacher education colleges.

Innovative pedagogy is needed as a means to actualize the vision to adapt the education system to the demands of the 21st century. The goal is to facilitate students' preparation for new challenges posed by the digital era and rapid socio‐economic change (Larson & Miller, 2011; Lim, Chai, & Churchill, 2011). Innovative pedagogy is defined as a planned set of educational activities that presents new ideas in a defined context, aiming to extensively improve the ability to learn within a situation of interaction; one of these can be the ClassBoost. Ideally, the process of knowledge construction should be anchored within a learning activity that is project based and focused on authentic real‐life problems (Fullan, 2009, 2013). Demands from teachers in light of the need for 21st century skills include creating a curriculum that is relevant to optimal functioning in the 21st century, which focuses on students' interests and on developing future skills; teaching; learning; and evaluation processes that are knowledge based, using information and communication technologies, which will highlight the student as the focus of the process, create motivation for learning, and emphasize active learning and diversity, as well as providing easy access to a variety of resources (Fullan, 2013; Kozma & Vota, 2014). The concept that an innovative pedagogical framework should be introduced in teacher education stems from an understanding of the mutual relations between pedagogy and the changing learning environment (Bower, Highfield, Furney, & Mowbray, 2013; Ertmer & Ottenbreit‐Leftwich, 2013; Torsani, 2016).

The national education programme “Israel moves to a higher grade” employs innovative pedagogy to create meaningful learning. The goal of this meaningful learning is to develop high‐order thinking skills, creativity, and self‐learning, to facilitate personal growth and social involvement, while strengthening the teacher as an educational leader of novel pedagogy (Banas & York, 2014; Barak, 2010), and this trend has not skipped over the colleges of education.

To summarize, the above review of relevant literature indicates that the ClassBoost system enables the recording of the lecturer's lesson during the lesson while permitting students' participation and learning based on mutual relations between learners and between the learners and studied learning materials. Education systems are currently coping with the need to improve technology in education in order to transmit and develop 21st century skills among the students and as part of the school culture. Teacher education colleges play an important role in training teachers and preparing them for the education system that now integrates technology in school teaching. An examination of the use of systems such as ClassBoost as part of the teacher education process can serve as a test case for the examination of students' perceptions regarding the use of this system as a tool during their teacher education.

It is hoped that experiencing the use of technological systems during the teachers' training process will also influence student teachers' willingness to integrate technology in their future work as teachers. This research aimed to investigate student teachers' perceptions concerning the use of the ClassBoost system in a teacher education college, as it affected the extent of their participation in their learning and the collaborative learning that the system enables.

2.4 The research goal

The research focused on student teachers, who were exposed to the use of the ClassBoost system during their teacher education process in an academic college of education in Israel. The research aspired to analyse the system's pedagogic qualities, at the inception of its introduction into the college, with emphasis on the students' collaborative learning patterns skills and learning practices as perceived by the student teachers themselves, and this is its unique contribution. Focusing on the student teachers, the research was able to examine their attitudes towards the use of the ClassBoost system and its influences on their learning. Therefore, the research questions were

1. How do the student teachers perceive the use of the ClassBoost system and its influences on their learning?
2. How do the students experience the use of the ClassBoost system as an innovative learning means that encourages collaborative learning practices?

3.1 The research context

The research was conducted in one of the 27 academic colleges in Israel that train teachers for the education system. The college sees it as its mission to advance the assimilation of innovative technologies in teaching and learning. The college classrooms are equipped with the latest technological means, but the processes for assimilation of this technology are still in their infancy. In Israel, as in other world states, the teacher education system has been undergoing reform in the attempt to prepare new teachers with 21st century skills and to equip them with tools for the digital age (Forkosh‐Baruch, Mioduser, & Nachmias, 2012; Larson & Miller, 2011). This work is accompanied by many difficult dilemmas (Beach, Henderson, & Finkelstein, 2012).

The Israel Ministry of Education's national programme, “Israel moves to a higher grade,” proposes the use of innovative pedagogy in order to produce meaningful learning, in which the student asks questions, gathers information resources, processes information, and creates new knowledge that is relevant to his or her personal world and for life in the digital era of the 21st century.

The present study was carried out in 2016, which was the second year of the college's use of the ClassBoost as part of the college's preparations for adaptation to the digital era (Levin & Tsybulsky, 2017). The ClassBoost system was installed in the college in two classrooms and used during most of the study hours. In the year when the research was conducted, 15 courses were held in the classes with the ClassBoost system. Six hundred students studied courses in these classrooms after a short briefing about the system.

3.2 Research type

This was mainly a quantitative study, based on the analysis of responses to questionnaires, which asked the student teachers about their learning patterns and their use of the ClassBoost system during their academic studies as part of their teacher education process. Qualitative data from responses to the open questions in the questionnaire are presented below in the report on the research findings to reinforce results identified in the quantitative data. However, as noted, the present article mainly reports findings from the quantitative part of the questionnaire.

The research data were derived from responses administered at two measuring points, as detailed below. The data underwent statistical analyses including descriptive statistics, comparison of means for independent samples using t tests and Pearson correlation coefficients, with the aim of examining correlations between pairs of variables. Analysis of the qualitative data was performed with Atlas7 software, extracting categories, by sorting the responses into statements to form categories, quantifying the number of statements in each category, and considering the value of each category relative to all the statements.

3.3 The research population

The samples for both stages of the research, at the beginning and end of the year were administered to the 600 students via email. The sample's segmented characteristics represent the distribution of the population that studies at the teacher education college.

The sample for the first measuring point at the beginning of the academic year, included 121 respondents from a total of 600 students (20%), who studied in those courses that used the ClassBoost system. Most of them were female (85.1%), most of them were bachelor's degree students (52.9%), and the remainder were studying in an academic retraining course (19.8%) or in master's degree courses (27.3%); 29% of the respondents were studying in the Special Education stream and 26% in the Administration, Education Systems, and Human Resources units. The proportion of respondents studying in other units was lower (10%—History, 8%—Linguistics and Literature, 7%—Sciences, 7%—the Early Childhood unit, 6%—Social Sciences or Humanities, 6%—Multidisciplinary or Special Courses such as “30+,” and 4%—Mathematics).

The sample for the second measuring point included 126 respondents from a total of 600 students (21%) studying in the courses that used the ClassBoost system. Most respondents were women (87.3%). Most of them were bachelor's degree students (57.1%), and the remainder were studying in an academic retraining course (20.6%) or in master's degree courses (18.3%).

There were five respondents whose academic stream was unidentifiable, so these respondents were excluded from the rest of the analysis, and it was decided that the analyses would relate to 121 respondents; 32% of the respondents were studying in the Special Education stream—this was the most prevalent stream among the respondents. In contrast to the sample at the first measuring point, it was found that at the end of the year, 20% of the respondents were studying Linguistics and Literature and 19% were studying in the Administration, Education Systems, and Human Resources units. The proportion of respondents studying in other units was lower (10%—Early Childhood, 8%—History, 5%—Mathematics, 3%—Social Sciences and Humanities). Especially low proportions were studying Sciences (2%) or General Studies (2%).

3.4 The research procedure

As noted, the research relied on data from two questionnaires completed by the student teachers studying during the relevant semesters in their classrooms: one questionnaire at the beginning and then another questionnaire at the end of the academic year. The intention was to compare the student teachers' attitudes during their first session of the course and to evaluate their attitudes concerning the use of the system at the end of the course. It was assumed that there would be a difference between attitudes before getting to know the system and attitudes after using the system in course lectures throughout the course. The questionnaire was administered to the students through a link to a Google form.

3.5 The research tools

The research tool was a self‐report questionnaire for the course students. The questionnaire included a closed part with multi‐choice answers to questions and statements necessitating marking of attitudes on a 5‐point Likert scale. One open‐ended question asked whether the students perceived the advantages of the system as a means to promote learning at the different stages of their use of the system.

The questionnaire was developed on the basis of interviews with student teachers who had experienced learning in a classroom where the system was installed and interviews with lecturers teaching in this classroom. Two researchers, both senior faculty members and lecturers in the college, validated the contents of the questions and the final version of the questionnaire was administered as a pilot test to 10 student teachers in order to verify that the items were clearly understood by them.

4.1 The use of the ClassBoost system and its influences on the student teachers' learning

Varimax rotation factor analysis conducted to characterize the respondents' attitudes towards the use of the ClassBoost system identified three main categories that together explain 67.8% of the common difference: (a) the influence of the ClassBoost system on students' attendance in the courses, (b) the positive contribution and influence of the ClassBoost system on students' learning, and (c) resistance and undesirable aspects of the ClassBoost system for learning.

The first factor included one statement relating to negative influence of the use of the system on students' attendance in the courses. The statement was “following the use of the ClassBoost system in the course, students' attendance in the course will lessen.” The respondents' mean grade for this statement was M = 2.59 (SD = 1.12), indicating a medium‐low level influence of the system on the reduction of students' physical attendance in the course.

The second identified factor related to the positive contribution of the ClassBoost system to learning and also to positive aspects that were expected to appear result from its use. Examples of statements in this context: “In general, there is a strong possibility that the use of the ClassBoost system will improve the quality of learning in the college,” “there is a strong possibility that the use of the ClassBoost system will improve teaching quality in the college,” and so forth. Cronbach's α for the relevant statements in this index was α = 0.949, indicating a high level of internal consistency for the items in the index. Analysis of the respondents' attitudes showed a mean grade for answers M = 3.84 (SD = 0.95) indicating a medium‐high contribution (relative to the index scale) by the system to learning.

The last factor that emerged from the factor analysis signified resistance to the use of the ClassBoost system and negative aspects that could stem from its use. Examples of the statements in this context were “I find it difficult to adapt to the use of the ClassBoost system” and “the use of the ClassBoost system arouses my sense of resistance.” Cronbach's α for the relevant statements in this index was α = 0.883 indicating a high level of internal consistency for the items in the index. Analysis of the respondents' attitudes showed that the mean grade for answers, M = 1.38 (SD = 0.58), indicated a low level of resistance regarding use of the system and also a perception of negative characteristics associated with the use of the system that were very low relative to the index scale.

Table 1 below summarizes the results of the Pearson correlation coefficients between respondents' attitudes concerning the use of the ClassBoost system as appeared in the first questionnaire.

The analysis shown in Table 1 indicates a positive correlation between evaluation of the extent of contribution of the system to learning and evaluation of the positive aspects associated with its use (r = .735, p < 0.01). Correspondingly, it was found that there was a negative correlation between evaluation of the contribution of the system to learning and evaluation of negative aspects associated with its use (r = −.461, p < 0.01).

No significant correlation was found between evaluation of the contribution of the ClassBoost system and evaluation of its influence on attendance in courses. Similarly, no correlation was found between evaluation of the influence of the use of the system on attendance in courses and evaluation of positive aspects associated with its use or with negative aspects associated with its use. Thus, the character of attitude towards the use of the system and its contribution is not connected to the evaluation of its influence on attendance in the courses. Finally, a significant negative correlation was found (r = −.599, p < 0.01) between evaluation of the positive aspects associated with the use of the system and evaluation of negative aspects associated with its use.

The respondents' attitudes concerning the use of the ClassBoost system were also examined at the second measuring point, at the year's end. First, the respondents were asked to evaluate the extent of contribution of the system to learning on a 10‐point scale. Analysis indicated that the respondents' mean grade was M = 7.03 (SD = 2.98). Consideration of the fact that this grade appeared a 10‐point scale indicates a medium‐level evaluation of the expected contribution of the system to learning. Later, the respondents were asked to evaluate additional aspects on a 5‐point scale (from 1 = completely disagree to 5 = agree to a very large extent). Confirmatory Factor Analysis was conducted, to recharacterize the respondents' attitudes towards the ClassBoost system. Results of this analysis indicate that two factors together explained 64.4% of the common difference: (a) the contribution and positive influence of the ClassBoost system on learning and (b) resistance and undesirable aspects associated with ClassBoost for learning.

With regard to the first factor and in light of the statements presented before in this context, it was found that Cronbach's α value for the index was α = 0.960, indicating a high level of internal consistency for the items on the index. Analysis of the respondents' attitudes revealed a mean grade of M = 4.05 (SD = 0.95) indicating a perception that the contribution of the system to learning was seen as at a high level in relation to the index scale.

The second factor that emerged from the factor analysis represented resistance to the use of the ClassBoost system and negative aspects that could stem from its use. The second factor included the statements presented above in this context. Cronbach's α for the relevant statements on this index was α = 0.836, and this indicates that the index items had a high level of internal consistency. Analysis of the respondents' attitudes revealed a mean grade of M = 1.43 (SD = 0.54) indicating that the level of resistance to the use of the system, like their perception of negative characteristics associated with the use of the system, was very low relative to the index scale.

From the results of the Pearson correlation coefficients between the respondents' different attitudes concerning the use of the ClassBoost system, it appears that there was a positive correlation between the evaluation of the extent of contribution by the system to learning and evaluation of positive aspects associated with its use (r = .729, p < 0.01). Correspondingly, a negative correlation was found between the evaluation of the contribution of the system to learning and evaluation of negative aspects associated with its use (r = −.452, p < 0.01). Thus too, a significant negative correlation was found (r = −.557, p < 0.01) between evaluation of positive aspects associated with the use of the system and evaluation of negative aspects associated with its use.

4.2 Characteristics of the students' collaborative learning

At the end of the academic year, the student teachers were asked to complete an additional questionnaire, which aimed to understand the characteristics of learning with ClassBoost, especially relating to learning that included innovations and involved and encouraged collaboration and interactivity. It is noted that the questionnaire relating to collaborative learning was only administered at the second measuring point, because at this point, it was relevant to ask the students about their experience in learning with the system and the implications of this learning together with innovative technologies and implications of these experiences on their collaborative learning. In this context, the students were asked to relate to 21 statements, as detailed in Table 2 below, on a 5‐point scale (1 = agree, 5 = do not agree). Table 2 shows the results of the Varimax rotation factor analysis to identify factors with loaded Eigenvalue higher than 2. The results of the analysis indicate the existence of three distinct factors that explain 51.76% of the common difference.

As shown in Table 2 above, the first factor that was identified related to aspects of “innovation in college learning” and this factor included aspects relating to the way in which innovation is assimilated in the college's learning environment. The reliability of this factor, α = 0.875, is high, indicating a high level of internal consistency of the items. The mean value of the variable that was calculated according to this combination is M = 3.405 (SD = 0.890) indicating a medium‐high level of innovation in the college's learning environment in relation to the index scale.

The second factor that was identified relates to aspects associated with “collaborative learning.” The reliability of the variable, calculated according to Cronbach's α was α = 0.850, indicating a high level of internal consistency of the items. The mean value of the answers received in this context was M = 3.176 (SD = 0.672), indicating a medium level of collaboration in the college's learning environment.

The third factor that was identified relates to “face‐to‐face collaborative learning.” The reliability of this variable was α = 0.649, a value considered acceptable for the estimation of the variable's reliability. The respondents' answers for these aspects were at a medium‐high level (M = 3.826; SD = 0.383) indicating that this is the level of collaborative learning in the college.

4.3 Comparative analyses

Pearson's correlation coefficients were calculated, in order to understand the character of interrelations between the different aspects of the use of the ClassBoost system and also the correlations between these aspects and characteristics of the perception of collaborative learning in the college. The results of this analysis appear in Table 3 below.

The analysis shown in Table 3 indicates the existence of significant positive correlations between the perception of the extent of contribution by the ClassBoost system and the perception of innovation in the college (r = .418, p < 0.01). The learning environment was perceived as encouraging collaborative learning (r = .282, p < 0.01), and there was collaborative learning during the lessons (r = .231, p < 0.05). Similarly, significant positive correlations were found between the respondents' positive attitudes towards the ClassBoost system and the perception of innovation in the college (r = .340, p < 0.01), the perception of the learning environment as encouraging collaborative learning (r = .319, p < 0.01), and also the perception of collaborative learning during the lessons (r = .275, p < 0.01).

Contrastingly, no significant correlation was found between negative attitudes towards the ClassBoost system and collaborative learning characteristics in the college, except for a significant negative correlation (r = −.211, p < 0.05) between negative attitudes towards the system and the perception of the college learning environment as encouraging collaborative learning. Here, perhaps, is the place to clarify that analysis also revealed the existence of significant positive correlations between the perceived characteristics of the college's collaborative learning environment. In this frame, a significant positive correlation was found between the perception of innovation in the college and the perception of a learning environment that encouraged collaborative learning (r = .371, p < 0.01) and also between the perception of innovation in the college and attitudes towards the existence of collaborative learning as part of the lessons (r = .287, p < 0.01) and between the perception of online and social collaborative learning and collaborative learning during the lessons (r = .307, p < 0.01).

Here, it is important to note that these findings are partially supported by the responses to the qualitative part of the research (to be described in detail in another article) that examined students' views regarding the advantages of the use of the ClassBoost system as a means to promote learning at the different stages of use of the system. The advantages noted by the students were classified into three areas and represent the contribution of the system to learning processes and the students' collaborative learning practices: (a) advantages associated with the students and cognitive aspects of their learning processes (79% of the statements), (b) advantages associated with the students and emotional aspects of their learning processes (11% of the statements), and (c) advantages associated with personal and social facets of the pedagogic teaching–learning models (10% of the statements).

The following are detailed results for each category: (a) advantages associated with the student and cognitive aspects of the learning processes: filling academic gaps and deficits, repeated use of learning materials for clarification, sharpening and deepening understanding, and use of learning strategies enabling students to overcome attention and memory disabilities. Examples: “clarifying the material and being able to go back to whatever we haven't managed to write or understand in the lessons” and “if I forget something, I can always refresh my memory again.” (b) Advantages associated with the students and emotional aspects of their learning processes: the students mentioned their feelings of confidence, calmness and comfort due to the fact that all the materials studied in the course were uploaded and accessible for their use. Example: “I am calm because the material is recorded.” (c) Advantages associated with personal and social facets of the pedagogic teaching–learning models: with regard to the personal facet of the pedagogy, the system was seen as enabling distance learning, highlighting accessibility and flexibility. For example, “the system enables us to listen to the lesson at another more comfortable time and place.” The main most frequently mentioned advantage of the pedagogic model of distance learning was the comfort for the student and their style of learning. Additionally, the system was perceived as helping students' independent learning and self‐guidance through the learning process. The social facet of the pedagogy included collaborative learning. Collaborations were characterized by a most basic level of interaction for the purpose of knowledge sharing. There was almost no collaborative dialogue that structured new knowledge, to solve students' problems or to create products together through the system. With regard to psychological aspects, it was found that the motivation for collaborations was extrinsic and had no influence on the strengthening of intrinsic motivation. The sense of social cohesion that students felt in the classroom, remained within the boundaries of the classroom's physical space and did not permeate the virtual space.

5.1 Students' attendance during the course

It seems that the ClassBoost system did not influence the students' physical presence in the course at either of the measuring points, at the beginning and end of the course, as was found in previous research (Nashash & Gunn, 2013; Toppin, 2011).

5.2 Contribution to learning

It was also found that students felt that the use of the ClassBoost system contributed to their learning, especially because it improved the quality of classroom teaching. In other words, the students perceived that there was an improvement in classroom teaching, apparently because of what the ClassBoost system qualities allowed them to do. Advantages relating to cognitive aspects of the system emerged from the qualitative part of the research. The students mentioned supplementation, repetition, clarification, and deepening of the studied materials as activities that contributed to their learning. Additionally, the students reported a sense of confidence, calm, and comfort because the learning materials were easily accessible; in this way, they expressed the emotional advantages of the system.

At the second measuring point, there was a relative reduction in the perception of a contribution by the ClassBoost system to learning from the student teachers' viewpoint. This aspect is in line with the findings of previous research, which found that use of LCT was not expressed in alterations in the learners' achievements (Bollmeier et al., 2010; Drouin, 2014; Hadgu, Huynh, & Gopalan, 2016; Pale et al., 2014). We estimate that the reduction in the perception of the contribution of the ClassBoost system to learning is also connected to the fact that not all the qualities of the ClassBoost system were exploited, and the students did not know about or were not exposed to all the means and possibilities of this system. It is important to note in this context that the ClassBoost system is still in early stages of assimilation in the studied college.

5.3 Resistance regarding the use of the system

It was also found that the use of the ClassBoost system was seen as having relatively low negative implications both at the beginning and end of the year, meaning that the students did not appear to have any fear or resistance regarding the use of the ClassBoost system as one of the innovative technological tools offered by the college and accessible to them during their studies (Newton et al., 2014).

5.4 Collaborative learning

The findings also show that when considering the ClassBoost system as a novel learning means that encourages collaborative learning practices, the students perceived their studies in the college as learning in an environment that integrates innovative technology to a medium‐high extent and providing virtual sites that accompany the course. The exams were seen as also using these innovative tools.

With regard to the student teachers' perceptions of their collaborative learning in the college's courses, it was found that they only evaluated collaborative learning at a medium level, whereas face‐to‐face collaborative learning was perceived as at a medium‐high level. The student teachers revealed willingness to integrate collaborative technology in their learning (Roblyer et al., 2010), but as emerged from the qualitative part of the present research and from previous studies, their collaborative learning practices focused on communication and sharing knowledge at the most basic level (Romero & Lambropoulos, 2011) and did not develop to the stage of shared construction of ideas and problem‐solving (Inayat et al., 2013). The motivation for collaborations was extrinsic and did not cause a change in practices (Pale et al., 2014). The ClassBoost system is based on 21st century skills, including collaborative learning practices and emphasis is given to the affinity between pedagogy and a dynamically changing learning environment (Bower et al., 2013; Ertmer & Ottenbreit‐Leftwich, 2013; Sadaf et al., 2016; Tondeur et al., 2016). Despite easy access to collaborative resources offered by the system, the use of the system did not provide emphasis for the learner as the center of the learning process (Fullan, 2013; Kozma & Vota, 2014). Like the practical suggestions that Torsani (2016) proposed for the integration of technology by language teachers, the present research findings also point up the need to integrate technology in learning processes, a subject that is increasingly prevalent in teacher education programmes throughout the world.

It seems from the research findings that, in general, the ClassBoost system encourages collaborative learning. It is clear that it is used both on the system level and at the lesson level. Nevertheless, it seems that the potential of collaborative learning was not sufficiently exploited by the studied college. As was found by Fischer et al. (2013), cooperation that stems from extrinsic motivation may alter computer‐assisted collaborative learning patterns and influence the development of cooperation out of the learner's intrinsic motivation. At this point, a new issue rises to the forefront of the discussion, suggesting directions for future research: the role of lecturers who teach in classes with the ClassBoost system as agents of change encouraging high‐order collaborative learning.

To summarize, this research focused on the viewpoints of student teachers studying in an academic college of education with an emphasis on their attitudes towards the use of the ClassBoost system. It therefore differs from other studies that focused on the implications of the use of the LCT system for learners' achievements, attendance in lessons, their learning styles, and objective measures of their learning. The researchers would like to emphasize that the main finding that emerged from this research clarifies the implications of use of the ClassBoost system for the preparation of teachers for the education system. The uniqueness of this study stems from the fact that it throws light on implications of learning assisted by innovative technology in teaching, such as the ClassBoost system among student teachers training for teaching and indicates that this may stimulate their own assimilation of innovative technology that encourages collaboration in their school teaching.

5.5 Practical implication

Given the findings of Newton et al. (2014) and considering the findings of the present study, the process of assimilation of innovative technology is clearly a long, complex process, and results are not always according to expectations. The characteristics of these technologies do not always lend themselves to satisfactory results, and it is recommended to try to increase satisfaction regarding the system while simultaneously mediating the characteristics of the system and its benefits to the students. When the students are unaware of the special qualities of the system, they are unable to enjoy maximum benefits, and so it is worthwhile to provide specific guidance so that they can recognize the system's potential for learning. It is also suggested that teacher educators teaching with the system should undergo intensive instruction, and they can then help students to maximize their exploitation of the possibilities that the system offers for learning.

5.6 Limitations of the research and suggestions for further investigation

The present study focused on student teachers during the process for teaching in an academic college of education, and this is its unique contribution. However, the study was conducted at the beginning of the process of introduction of innovative technology such as the ClassBoost system in the college. It would be valuable to continue to investigate the implications of this system for the student teachers in the future and to examine the consequences of the use of the system on the students' own abilities to integrate innovative technologies in their school teaching. Moreover, it is suggested that future research should pose similar questions to those posed in the present study to teachers in higher education institutions (Shagrir, 2017).