This study explores the use of technology in the design of learning activities by Russian teachers and their relationship with the technology self-efficacy in higher education. The Inventory of Learning Activities with Technologies in the University was translated and adapted to Russian context and validated by retest method. Answers were classified through content analysis. Findings suggest that access to technology, on-line courses, and data elaboration software among teachers should be enhanced. Teachers' self-confidence and use of technologies are related: one increases the level of another and vice-versa.
Since supercomputing is considered a strategic area [
The skills necessity claim of specialists in supercomputing [
Studies on the learners and the teachers could help to determine if they are ready for a new technology [12]. Student-centered approaches to learning have encouraged teachers to integrate technologies into their teaching. Empirical research reported that teacher attitudes and personal use of technology, accounted for 55% of the variance [13]. Considering teachers as facilitators, the incorporation of technology into their teaching is critical [14]. In fact, it is necessary to understand how the implementat ion of a technology could improve the perceived competence and use of teachers in their teaching [15]. Recent research to determine the possibilities of using technology in high education highlighted the increase of favorable circumstances for a professional competency development [16]. From a technology-enhanced learning perspective, understand the reasons of teachers using or not technology and what they should know in order to use it, requires further research [17, 18]. In this context, teachers requirement of more preparation is a relevant issue in Russia [19]. Moreover, what technologies do Russian teachers use related to learning activities in HPC is missing.
The "Inventory of Learning Activities with Technologies in the University" (IAATU) [20] is applied to assess what type of technology Russian university teachers are using to design learning activities and which is they level of self-confidence to use it. The problem of training specialists in the field of supercomputing has been widely discussed but, no from this perspective. This study is a contribution to new knowledge in the field of HTC, from the approach of teacher attitudes, specifically confidence , with the use of technology in the design of learning activities.
2.1.
The HPC concept circumscribes the computer server systems market, software, networking and services used to manage
computationally intensive, data simulation and analytic problems [
Nevertheless, not all is about tools [
Data Science / R. Martinez-Lopez, C. Yot, M. Sacchini
technique [
Despite the recognition of HPC based simulation as belonged to the scientific inquiry and recommendations of integrating
computational science methods in universities [
Instead of focusing in “what should we teach” or “what should be included in the new curricula” [
Teachers are one of the target groups of supercomputing education infrastructure [
Through IAATU, this study explores the use of learning activities with technologies and self-confidence by teachers at Russia universities.
In the original study, 103 answers were collected from the online survey, since February to April, 2016. 52.4 % females and, 47.6 % males. 43.7%, in the age group of 31-40, 17.5 under 31 and 9.7% over 61. 44.7% of the teachers from Russia Universities. Re-test (n=48) was realized at Samara National Research University. 47,9% women and 52,1% men. In relation to age 16,7% between 20 and 30 years old, 27,1% (31-40), 27,1% (41-50), 12,5% (51-60) and 16,7% (61-70).
In order to explore to what extent university professors are using technology as a pedagogical support resource, IAATU was used [20]. The adapted Russian version of IAATU [28], with 38 items distributed among 1 to 5 on a double Likert-type scale, collect demographic information such as: gender, age, university, field of knowledge and professional category. One scale refers to use frecuency asking “to what extent do you perform the activities described in the item?” while the other refers to the degree to which the teacher feels confident using the technology with the question “If you perform them, to what extent do you feel comfortable?” Two open questions in relation to technology not included and the use of technology at the University, are contemplated.
3.1.
Descriptive statistical methods were employed to analyze the level of the participants in self-confidence and in the use of technology. IBM SPSS Statistics and univariate were used to describe the characteristics and activities learning technologies frequency of the participants. In addition to pretest the Russian target language version of IAATU, re-test with target language subjects was conducted [23]. Temporal stability of the responses were analyzed on the same group of respondents with an interval of one month by means of a method based on the use of IAATU [24]. Moreover, the correlation coefficient between the two intervals of IAATU were examined [25], through Pearson Correlation Coefficient. Likewise, considering coefficient alpha and retest as index of reliability, were calculated [25]. The estimated internal consistency of each scale in the retest is provided in order to increase confidence in measure [26]. A Spearman's correlation was run to assess the relationship between technology use in learning activities and self-confidence on that technology, of a small sample of 48 teachers aged 31-50 years old at Samara National Research University.
Data Science / R. Martinez-Lopez, C. Yot, M. Sacchini
In order to analyze the content of open questions a frequency criterion was adopted. That is, higher was the number of the repetition of the same or similar terms in the answers, higher was the importance of such words. In this case, the words of the answers were also to be evaluated as word-concepts to count in order to establish which specific problems of access to technology are present among the teachers of Russian Universities. For example we got a word-concept as <lack of software> from analyzing and summing up an answer like: “I can not use technology in class, because there is no software to be used for economic tasks. Or at least I do not know them.”
Scales of level of use (Cronbach’s α = .91) and self-confidence (α = .93). Results re-test in relation to use (α = .93) and selfconfidence (α = .94) were reported with a value above Cronbach’s α = .95 scales. It showed very good reliability and internal consistency, which meets the criteria of reliability [27]. As previously reported, association between the use of learning activity and self-confidence in the Russian adaptation of IAATU were established [28].
The test-retest reliability coefficient of use scale (Figure 1) showed that there was a moderate positive correlation, which means there is a tendency for high use variable (n=103) scores of the original test go with high use (n=48) variable scores of retest (and vice versa), r = .56, p = < .001, with a R2 = .323. In the confident scale (Figure 2), there was a moderate positive correlation, which means there is a tendency for high self-efficacy variable in the original test (n=103) scores go with high selfefficacy variable scores in the re-test (n=48), and vice versa, r = .56, p = < .001, with a R2 = .322.
In relation to the re-test analysis, the average use and confidence score for each item were calculated (Table 1). Three groups of learning activities are identified in relation to the mean: low level (mean 1-2.5), medium (2.5- 3.5) and high (3.5-5). The average confidence is higher than the use. According to the same statistic (Table 2), up to 8 items have a high average use and confidence score (3.5-5). According with previous research, this results suggest that teachers' technology previous practice and confidence could determine their use of technology in their teaching [29].
In addition for five items, trust is high (3.5-5) and the use is medium (2.5-3.5): Item 4 “During my presentations and to facilitate my students’ understanding of given concepts and ideas, I use video segments found on Internet” (M=3.11 SD=1.18, M=4 SD=1.04), Item 6 “Using the virtual platform, I provide my students with videos, demonstrations, simulations, experiences and/or cases to expand the information they received” (M=2.52 SD=1.41, M=3.56 SD=1.48), Item 9 “I select text documents and I make them available to my students on the virtual platform in an effort to improve the reading understanding of my subject ,287 ,066 ,766 ,000 ,908 ,000 ,483 ,001 ,731 ,000 ,839 ,000 ,698 ,000 ,719 ,000 ,603 ,000 Item 32 ,919 ,000 ,625 ,000 ,929 ,000 ,752 ,000 ,720 ,000 ,667 ,000 ,723 ,000 ,541 ,002 ,890 ,000 ,925 ,000 ,845 ,000 ,791
0 ,913 ,000 Item 30 ,812 ,000
Item 31 ,803 ,000
Item 33 ,949 ,000
Item 34 ,910 ,000
Item 35 ,664 ,000
Item 36 ,971 ,000
Data Science / R. Martinez-Lopez, C. Yot, M. Sacchini content” (M=3 SD=1.53, M=3.78 SD=1.45), Item 13 “I design practical cases, using digital resources (videos, presentations, specific software, etc.), so that students can apply the theory learned to practical cases” (M=3.25 SD=1.37, M=3.95 SD=1.18), Item 22 “I design problems in which students have to solve complex problems, using digital resources, similar to those a professional would use” (M=3.38 SD=1.56, M=3.95 SD=1.37). Further research would be necessary in order to explore the reasons of this dissonance.
Spearman correlation (Table 1) was calculated. There was a strong positive correlation between use of technology and selfconfidence, which was statistically significant, rs = .7217, p = .0 in all cases, except for item 3 (M=3.65 SD=1.15, M=4.38 SD=0.85), “During my presentations, I show students some type of simulations, demonstrations or examples based on digital resources, either my own, or available on the web, to clarify concepts and ideas”. Unlike the initial results, the strength o f the association of the items is not coincident in most cases. It would be necessary further research in order to determine the reasons.
According to the Mann-Whitney U tests only the level of use of item 18 “I design activities in which students must provide comments or given their point of view by means of personal or group blogs” differs according to sex (sig. 0.32). The confidence level of items 17 “I facilitate interaction with students outside the classroom by means of cellphone applications such as WhatsApp, Line, Twitter, Facebook, etc. to motivate the exchange of information, the resolution of doubts…” (sig. 0.15), 18 “I design activities in which students must provide comments or given their point of view by means of personal or group blogs” (sig. 0.15), 29 “I use virtual platform tools so that students can turn in homework/papers for my subject” (sig. 0.40), 30 “When assessing students, I use electronic portfolios, created on the actual platform or with specific online tools, for continual assessment” (sig. 0.002) differ according to gender. According to Kruskal, the level of use of items 20 “I ask students to write reports, essays, articles, etc. using reference management tools such as Zotero, Refworks, Mendeley, Endnote...” (sig. 0.009) and 38 (sig. 0.039) differed according to age. Only the confidence of 38 “During my teaching activities, I attend the terms of use for the digital materials that have a Creative Commons license” (sig. 0.46) differed according to age.
In order to complete the study content analysis of open questions from the original study (n=103), (Table 3) and (Table 4),
following frequency criteria was applied. The first open question (Table 3) was: “If your learning process involves technologies
that are not listed in the questionnaire, please describe them”. It is highlighted that 6 answers specifically mentioned the System
Management Learning (LMS) Moodle, as a technology not mentioned in IAATU. Due to Moodle is the main LMS used in
Russian universities [30], and it is recommended in the learning administrative process and the training [
The second open question (Table 4) refers “If you want to leave a comment on the questionnaire with questions on the educational process with the use of technology at the University”. 13 answers mentioned the University as responsible of the use of technology by teachers. 9 of them referenced the lack of access and availability of technology and 3, training needs. [A1] count 2 comments of one person as 2
Analysis showed that the more frequent problems reported by teachers at Russian University are technology acknowledge
This allowed us to understand that at the present day Russian Universities suffers of an insufficient usage of technological
means and structures. Another problem connected to the access of technology could be explained also with the actual lack of
software knowledge of the newest technology adapted to be used for specific task in the didactic by the Engineering and
Economy Faculties. Related to this, it is recommended the application of collaborative pedagogical approaches after the
implementation of IT solutions [
The analysis of the self-confidence answer category cluster related to the teacher behaviour in relation to the use of technology for learning activities. 5 answers are related to the use of technology in relation to self-confidence, for example: “If I
Data Science / R. Martinez-Lopez, C. Yot, M. Sacchini do not use any technology, it is not always due to the fact that I don't feel comfortable with it I can not know it, or do not have access or do not have enough time to do it.” or “I can not use ready-made test (…)” and 1 to familiarity with ICT. 3 answers were a mix between comments in reference to the questionnaire (2), for example: “Not all the tools described in the questionnaire are familiar but, answers are formulated on the basis of analog products with similar functionality in the educational process”, “I do a lot of issues of teacher training and blended learning technology development of online courses so, I would be more interested in questions of technology implementation strategies (...)”; and the University (2), “I'm open and ready to cooperate with the organization in e-learning. They need to train teachers in online methodology”, “Lectures, laboratory and practices can not be transferred into the virtual space. Moodle is not available for all students”.
It is plausible that this research may have limitations that could have influenced the results obtained. First, the sample size of
our analysis are not enough to make generalizations about the more frequent problems reported by teachers at Russian
University. As such, the findings should be taken with caution. Second, the high value of no answers to the open questions can
be interpreted as perceived ambiguities in the meaning due to the fact that back-translation was not applied. Although it is not
considered mandatory [31], it provides an assertion that the instrument is the same in two languages [23]. Third, retest
assessments could introduce bias, due to the risk that respondents desire to appear consistent [32]. Furthermore, due to the
IAATU was translated into a new language, from Spanish to Russian, to avoid the assumption of hypotheses about the
dimensionality of a given set of items, exploratory factor analysis (EFA) could be applied [33]. Finally, considering that th e
support and maintenance of supercomputer centers require specific technology in order to automatic decision making on
emergency situations, monitoring, or high performance tasks for the infrastructure, and others [
Despite of the limitations, the results of this study coincide with previous research [34, 20] level of use of learning activity in
teachers depend on their technology self-efficacy [35]. Furthermore, IAATU could serve as a tool to identify teachers that
already have the attitude to serve as a bridge between the specialized knowledge of scientists and practitioners on the one hand,
and scholars [21]. Even more, further research could consider the identification of teacher profiles in relation to their lev el of use
of ICT in the design of learning activities [20]. Concerning to the use of digital technology, recent empirical studies pointed that
patterns of technology use emerge from the frequency of use and by the nature of the activity [36]. Similarly, IAATU could b e
applied to define what kind of learning activity teachers are using: lecturer’s presentation, communication, information
management, application, evaluative or productive [20]. Due to the recommendation of a collaborative learning approach in
supercomputing teaching [
Moreover, evidence has showed how teacher confidence in a task can be regulated by self-efficacy [37]. However, as confidence does not necessarily specify what the certainty is about [37], further data collection is necessary in order to determine exactly how confidence affects the use of technology in the design of learning activities at Russian Universities context.
This study contributes to the understanding of technology use and confidence (self-efficacy) in the design of learning
activities from the teacher perspective into the higher education system in Russia. Relationship between teachers’ own
technology practices and the type of technology activities they assign to students has been examined. From a competency-based
approach that acquires more holistic structure [38], this study highlight the importance of attitude, specifically, self-confidence
as complementary to skills and knowledge in HPC. Previous research pointed advanced training for university teachers in
various applied areas where supercomputing systems can be used for problem solving [
This work was supported by the Ministry of Education and Science of the Russian Federation and the 5-100 program. As part of first author’s doctorate thesis, the main author desires to transmit thanks to Professor Elenev Valeriy Dmitrievich, Director of the Institute of Aviation Technology at Samara National Research University, for invaluable support of this study.
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