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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">caer</journal-id><journal-title-group><journal-title xml:lang="ru">Central Asian Economic Review</journal-title><trans-title-group xml:lang="en"><trans-title>Central Asian Economic Review</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2789-4398</issn><issn pub-type="epub">2789-4401</issn><publisher><publisher-name>Университет Нархоз</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.52821/2789-4401-2022-6-163-174</article-id><article-id custom-type="elpub" pub-id-type="custom">caer-773</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>ЦИФРОВАЯ ЭКОНОМИКА</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>DIGITAL ECONOMY</subject></subj-group></article-categories><title-group><article-title>РОЛЬ ПРОГРАММЫ CANVAS В УСПЕВАЕМОСТИ СТУДЕНТОВ: МОДЕЛИ ПРИНЯТИЯ ТЕХНОЛОГИЙ И АКАДЕМИЧЕСКОГО СОПРОТИВЛЕНИЯ (НА ПРИМЕРЕ УНИВЕРСИТЕТА НАРХОЗ)</article-title><trans-title-group xml:lang="en"><trans-title>CANVAS PROGRAM ROLE IN STUDENTS' ACHIEVEMENT: TECHNOLOGY ACCEPTANCE AND ACADEMIC RESISTANCE MODELS (ON AN EXAMPLE OF NARXOZ UNIVERSITY)</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Ильясов</surname><given-names>Д. К.</given-names></name><name name-style="western" xml:lang="en"><surname>Ilyassov</surname><given-names>D.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Алматы</p></bio><bio xml:lang="en"><p>Didar Ilyassov – PhD student, candidate of economic science</p><p>Almaty</p></bio><email xlink:type="simple">didar.ilyassov@narxoz.kz</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru">Университет Нархоз<country>Казахстан</country></aff><aff xml:lang="en">Narxoz University<country>Kazakhstan</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2022</year></pub-date><pub-date pub-type="epub"><day>04</day><month>05</month><year>2023</year></pub-date><volume>0</volume><issue>6</issue><fpage>163</fpage><lpage>174</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Ильясов Д.К., 2023</copyright-statement><copyright-year>2023</copyright-year><copyright-holder xml:lang="ru">Ильясов Д.К.</copyright-holder><copyright-holder xml:lang="en">Ilyassov D.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://caer.narxoz.kz/jour/article/view/773">https://caer.narxoz.kz/jour/article/view/773</self-uri><abstract><p>Цель исследования – изучение жизнеспособности моделей принятия технологий (TAM) и академического сопротивления (ARM) для работы Moodle и Canvas в Университете Нархоз.Методология. Методологической основой исследования является опрос 9 педагогов. Интервью было посвящено восприятию и опыту преподавателей в использовании платформ Moodle и Canvas. Это исследование выдвинуло гипотезу о применении приложений TAM и ARM для использования Canvas.Вопросы были направлены на изучение того, как TAM и ARM могут объяснить практику преподавателей на платформах Moodle и Canvas. Затем данные, собранные в ходе интервью, были отправлены в Atlasti. Любая заинтересованность в использовании Canvas выявлен тематическим анализом.Оригинальность / ценность исследования. Простое использование TAM не работает должным образом для Canvas. Вклад этого исследования в существующую литературу заключается в том, что отсутствуют исследования по влиянию TAM и ARM на платформы Canvas в Университете Нархоз.Результаты исследования. В целом, большинство преподавателей удовлетворены качеством Canvas со следующими предложениями по улучшению:- Использование Canvas преподавателями, связанными с когнитивными и эмоциональными установками ARM, различно.- Дизайн курса имеет ту же структуру. Никакого другого воображения, связанного с дизайном курса, нет. Некоторые функции Canvas явно непонятны преподавателям.- Canvas должен помочь контролировать студентов из группы риска для поддержания их успеваемости. С этой точки зрения, система PLA (предиктивная аналитика обучения) должна работать, чтобы контролировать успеваемость студентов.</p></abstract><trans-abstract xml:lang="en"><p>The purpose of the study is to explore how Technology Acceptance (TAM) and Academic resistance (ARM) Models are working for Moodle and Canvas adoption at Narxoz University.Methodology. The methodological basis of the study is an interview of 9 teachers. The interview focused on the teachers’ perceptions and experience of using Moodle and Canvas platform. This study hypothesized TAM and ARM application for Canvas use.The questions aimed to explore how TAM and ARM could explain the teachers’ practice in Moodle and Canvas platform. Then data collected through interviews submitted to Atlasti. Any interest in using Canvas identified by Thematic analysis.The originality / value of the research. The easy use of TAM is not properly working for Canvas. The contribution of this study to existing literature will be that no outputs of how TAM and ARM are working related to Canvas platform at Narxoz University.Findings. In overall, most teachers are satisfied with quality of Canvas with some following suggestions for improvements:- The use of Canvas by teachers related to ARM cognitive and emotional attitudes are different.- The course design has the same structure. There is no any other imagination related to course design. Some functions of Canvas are obviously unclear for teachers.- Canvas should help monitor students at risk for support. From this point of view, PLA (predictive learning analytics) system should work to monitor students’ performance.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>модель принятия технологий (TAM)</kwd><kwd>модель академические сопротивления (ARM)</kwd><kwd>прогнозирующая аналитика обучения (PLA)</kwd><kwd>тематический анализ</kwd></kwd-group><kwd-group xml:lang="en"><kwd>Technology Acceptance Model (TAM)</kwd><kwd>Academic resistance Models (ARM)</kwd><kwd>predictive learning analytics (PLA)</kwd><kwd>thematic analysis</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Gasevic D., Dawson S., Rogers T. Learning analytics should not promote one size fits all: The effects of instructional conditions in predicating learning success // Internet and Higher Education. – 2016. – № 28. – P. 68-84. – DOI: https://doi.org/10.1016/j.iheduc.2015.10.002.</mixed-citation><mixed-citation xml:lang="en">Gasevic, D., Dawson, S. and Rogers, T. (2016). Learning analytics should not promote one size fits all: The effects of instructional conditions in predicating learning success. Internet and Higher Education, 28, 68- 84, DOI: https://doi.org/10.1016/j.iheduc.2015.10.002.</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Viberg O., Hatakka M., Bälter O., Mavroudi A. The current landscape of learning analytics in higher education // Computers in Human Behavior. – 2018. – № 89. – P. 98-110. – DOI: https://doi.org/10.1016/j.chb.2018.07.027.</mixed-citation><mixed-citation xml:lang="en">Viberg, O., Hatakka, M., Bälter, O. and Mavroudi, A. (2018). The current landscape of learning analytics in higher education. Computers in Human Behavior, 89, 98-110, DOI: https://doi.org/10.1016/j.chb.2018.07.027.</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Barney J. Firm Resources and Sustained Competitive Advantage // Journal of Management. – 1991. – № 17. – P. 1-20. – DOI: https://doi.org/10.1177/014920639101700108.</mixed-citation><mixed-citation xml:lang="en">Barney, J. (1991). Firm Resources and Sustained Competitive Advantage. Journal of Management, 17, 1-20, DOI: https://doi.org/10.1177/014920639101700108.</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Davenport T. H. Competing on Analytics // Harvard Business Review. – 2016. – № 84(1). – P. 98-107.</mixed-citation><mixed-citation xml:lang="en">Davenport, T. H. (2006). Competing on Analytics. Harvard Business Review, 84(1), 98-107.</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Shabbir M. Q., Gardezi S. B. Application of big data analytics and organizational performance: The mediating role of knowledge management practices // Journal of Big Data. – 2020. – № 7(1). – Article 47. – DOI: 10.1186/s40537-020-00317-6.</mixed-citation><mixed-citation xml:lang="en">Shabbir, M. Q. and Gardezi, S. B. (2020). Application of big data analytics and organizational performance: The mediating role of knowledge management practices. Journal of Big Data, 7(1), 47, DOI: 10.1186/s40537-020-00317-6.</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">Sekli G., Vega I. Adoption of Big Data Analytics and its impact on Organizational performance in Higher Education Mediated by Knowledge Management // Journal of Open Innovation: Technology, Market, and Complexity. – 2021. – № 2. – P. 1-20. – DOI: https://doi.org/10.3390/joitmc7040221.</mixed-citation><mixed-citation xml:lang="en">Sekli, G. and Vega, I. (2021). Adoption of Big Data Analytics and its impact on Organizational performance in Higher Education Mediated by Knowledge Management. Journal of Open Innovation: Technology, Market, and Complexity, 2, 1-20, DOI: https://doi.org/10.3390/joitmc7040221.</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Tiropanis T., Hall W., Crowcroft I., Contractor N., Tassiulas L. Network science, web science, and internet science // Communications of the ACM. – 2015. – № 58(8). – P. 76–82. – DOI: https://doi.org/10.1145/2699416.</mixed-citation><mixed-citation xml:lang="en">Tiropanis, T., Hall, W., Crowcroft, I., Contractor, N. and Tassiulas, L. (2015). Network science, web science, and internet science. Communications of the ACM, 58(8), 76-82, DOI: https://doi.org/10.1145/2699416.</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Pardos Z. A. Big data in education and the models that love them // Current Opinion in Behavioral Sciences. – 2017. – № 18. – P. 113-117. – DOI: 10.1016/j.cobeha.2017.11.006.</mixed-citation><mixed-citation xml:lang="en">Pardos, Z. A. (2017). Big data in education and the models that love them. Current Opinion in Behavioral Sciences, 18, 113-117, DOI: 10.1016/j.cobeha.2017.11.006.</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Laux Ch., Li N. Impacting Big Data analytics in higher education through Six Sigma techniques // International Journal of Productivity and Performance Management. – 2017. – № 66(5). – P. 15-21. – DOI: 10.1108/IJPPM-09-2016-0194.</mixed-citation><mixed-citation xml:lang="en">Laux, Ch. and Li, N. (2017). Impacting Big Data analytics in higher education through Six Sigma techniques. International Journal of Productivity and Performance Management, 66(5), 15-21, DOI: 10.1108/IJPPM-09-2016-0194.</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Drigas A. S., Leliopoulos P. The Use of Big Data in Education // IJCSI International Journal of Computer Science Issues. – 2014. – Vol. 11. – № 5(1). – P. 58-63.</mixed-citation><mixed-citation xml:lang="en">Drigas, A. S. and Leliopoulos, P. (2014). The Use of Big Data in Education. IJCSI International Journal of Computer Science Issues, 11, 5(1), 58-63.</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Herodotou Ch., Rientiis B., Boroowa A., Zdrahal Z., Hlosta M. A large‑scale implementation of predictive learning analytics in higher education: the teachers’ role and perspective // Educational Technology Research and Development. – 2019. – № 67. – P. 1-34. – DOI: 10.1007/s11423-019-09685-0.</mixed-citation><mixed-citation xml:lang="en">Herodotou, Ch., Rientiis, B., Boroowa, A., Zdrahal, Z., Hlosta, M. (2019). A large‑scale implementation of predictive learning analytics in higher education: the teachers’ role and perspective. Educational Technology Research and Development, 67, 1-34, DOI: 10.1007/s11423-019-09685-0.</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Davis F. D. Perceived usefulness, perceived ease of use, and user acceptance of information technology // MIS Quarterly. – 1989. – № 13(3). – P. 319–340. – DOI: 10.2307/249008.</mixed-citation><mixed-citation xml:lang="en">Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340, DOI: 10.2307/249008.</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Davis F. D., Bagozzi R. P., Warshaw P. R. User acceptance of computer technology: A comparison of two theoretical models // Management Science. – 1989. – № 35(8). – P. 982-1002. – DOI: https://doi.org/10.1287/mnsc.35.8.982.</mixed-citation><mixed-citation xml:lang="en">Davis, F. D., Bagozzi, R. P. and Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1002, DOI: https://doi.org/10.1287/mnsc.35.8.982.</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Teo T., Zhou M. The influence of teachers’ conceptions of teaching and learning on their technology acceptance // Interactive Learning Environments. – 2016. – № 25(4). – P. 513-527. – DOI: 10.1080/10494820.2016.1143844.</mixed-citation><mixed-citation xml:lang="en">Teo, T. and Zhou, M. (2016). The influence of teachers’ conceptions of teaching and learning on their technology acceptance. Interactive Learning Environments, 25(4), 513-527, DOI: 10.1080/10494820.2016.1143844.</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">Bandura A. Theories of Cognitive Self-Regulation // Organizational Behavior and Human Decision Processes. – 1991. – № 50(2). – P. 248-287. – DOI: https://doi.org/10.1016/0749-5978(91)90022-L.</mixed-citation><mixed-citation xml:lang="en">Bandura, A. (1991). Theories of Cognitive Self-Regulation. Organizational Behavior and Human Decision Processes, 50(2), 248-287, DOI: https://doi.org/10.1016/0749-5978(91)90022-L.</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Mergel I. Big Data in Public Affairs Education // Journal of Public Affairs Education. – 2016. – № 22(2). – P. 928-937. – DOI: 10.1111/puar.12625.</mixed-citation><mixed-citation xml:lang="en">Mergel, I. (2016). Big Data in Public Affairs Education. Journal of Public Affairs Education, 22(2), 928-937, DOI: 10.1111/puar.12625.</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
