研究生: |
羅彥婷 Lo, Yen-Ting |
---|---|
論文名稱: |
利用AI工具協助高中生英文寫作能力之後設認知力、科技創新意識、自我效能、趣味與求知價值及學習表現提升 Using AI Tools to Enhance High School Students' English Writing Abilities in Relation to Metacognitive Skills, Innovativeness, Self-efficacy, Hedonic and Epistemic Value, and Learning Performance |
指導教授: |
洪榮昭
Hong, Jon-Chao |
口試委員: |
洪榮昭
Hong, Jon-Chao 戴孜伃 Tai, Tzu-Yu 羅美蘭 Lo, Mei-Lan |
口試日期: | 2024/06/27 |
學位類別: |
碩士 Master |
系所名稱: |
創造力發展碩士在職專班 Continuing Education Master's Program of Creativity Development |
論文出版年: | 2024 |
畢業學年度: | 112 |
語文別: | 中文 |
論文頁數: | 124 |
中文關鍵詞: | 英文寫作 、生成式人工智慧 、後設認知 、科技創新意識 、AI 自我效能 、趣味性價值 、求知性價值 、學習表現 |
英文關鍵詞: | English writing, ChatGPT, metacognition, technological innovation awareness, AI self-efficacy, hedonic value, epistemic value, learning performance |
研究方法: | 準實驗設計法 |
DOI URL: | http://doi.org/10.6345/NTNU202401003 |
論文種類: | 學術論文 |
相關次數: | 點閱:236 下載:0 |
分享至: |
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
在台灣的高中生面臨學科能力測驗的情況下,英文寫作一直都是在英文學科中帶給學生及現場教師極大挑戰的一部分,教師面臨學生人數眾多、批改壓力繁重、批改標準難統一標準化等困擾,而學生端面臨回饋不即時、寫作興趣不高、後設認知不足、自我效能感受不彰等挑戰。傳統英文寫作教學中常使用的同儕互評亦因學生專業素養不足、人際互動壓力,在現場的執行效果有限。自2022年ChatGPT等AI工具的推出後,各界爭相使用並期望測試其效能,其中不乏各種教育相關的應用。本研究以新竹某高中學生為研究對象,期望透過引入AI工具,改善上述英文寫作的困難點,提供更具趣味和個人化的學習。透過AI工具,本研究期望探討學生的後設認知能力、科技創新意識、AI自我效能、趣味和求知價值,和學習表現之間的相關性。這項研究將對高中英文寫作教學和學生學習帶來有益的啟示,並有望為AI工具在教育領域的應用提供實證基礎。本研究使用實驗研究和問卷調查法,採立意取樣,邀請新竹地區某公立高中學生為研究對象,為期八週。問卷係經參考相關文獻後編制,包含「後設認知力」、「科技創新意識」、「自我效能」、「體驗價值-趣味價值」和「體驗價值-求知價值」量表。透過 SPSS 23與Smart PLS 執行結構方程模式分析及驗證。得到以下研究結果:
一、 後設認知力與ChatGPT自我效能呈正相關
二、 科技創新意識與ChatGPT自我效能呈正相關
三、 ChatGPT自我效能與求知性價值呈正相關
四、 ChatGPT自我效能與趣味性價值呈正相關
五、 求知性價值與學習表現不具相關性
六、 趣味性價值與學習表現呈負相關
七、 在差異性分析的結論則得出,原先英文成就分別為低中高之受測者在後設認知力、ChatGPT自我效能、學習表現進步量三構面都有顯著差異
Since the introduction of AI tools like ChatGPT in 2022, there has been a widespread adoption in various fields, including education. This study focuses on high school students in Hsinchu, aiming to address the difficulties in English writing by introducing AI tools to provide a more interesting and personalized learning experience. Using AI tools, this study aims to explore the correlation between students' metacognitive abilities, technological innovation awareness, AI self-efficacy, interest, intrinsic value, and learning performance. The findings of this research are expected to provide valuable insights for high school English writing instruction and student learning and contribute empirical evidence to the application of AI tools in the field of education. This study employs experimental research and questionnaire surveys, utilizing purposive sampling to invite high school students from a public school in Hsinchu as research participants over an eight-week period. The questionnaire, developed with reference to relevant literature, includes scales for "metacognitive ability," "technological innovation awareness," "self-efficacy," "experiential value – interest value," and "experiential value – intrinsic value." Structural equation modeling analyses and validations were conducted using SPSS 23, and Smart PLS. The following research results were obtained:
1. Metacognitive ability is positively correlated with ChatGPT self-efficacy.
2. Technological innovation awareness is positively correlated with ChatGPT self-efficacy.
3. ChatGPT self-efficacy is positively correlated with epistemic value.
4. ChatGPT self-efficacy is positively correlated with hedonic value.
5. Epistemic value is not correlated with learning performance.
6. Hedonic value is negatively correlated with learning performance.
7. The analysis of differences concluded that based on the participants' initial English performances, differences in the three dimensions of metacognitive ability, ChatGPT self-efficacy, and the improvement of scores are shown.
王志美、葉貞妮 (2021)。 科技創新意識, 主觀規範,滿意度與持續使用意願之研究:以美食外送平台為例。 中科大學報, 8(1), 1-24。https://doi.org/10.6902/JNTUST.202112_8(1).0001
吳明隆 (2013)。 結構方程模式: 潛在成長曲線分析。 五南圖書出版股份有限公司。
林育妡 (2008)。 認知策略在寫作教學之應用。 國小特殊教育, (46), 102-109。 https://doi.org/10.7034/SEES.200812.0102
邱皓政 (2017)。 多元迴歸的自變數比較與多元共線性之影響: 效果量,優勢性與相對權數指標的估計與應用。 NTU Management Review, 27(3)。https://doi.org/10.6226/NTUMR.2017.JAN.A103-022
張偉豪 (2011)。 SEM 論文寫作不求人。 三星統計發行。
許瑞郁(2024)。Cool English平臺運用於英文學習扶助課程。師友雙月刊,643,99-102。 https://doi.org/10.53106/266336712022070633020
郭旭展、陳逸萱 (2023)。 整合 AI,數位科技於創新教育課程設計與實踐。 Journal of Education Research (1680-6360),355。 https://doi.org/10.53106/168063602023110355002
陳昇瑋、溫怡玲(2019)。人工智慧在台灣: 產業轉型的契機與挑戰。天下雜誌。
黎瓊麗(2004)。技職院校大專學生英文寫作錯誤之分析與探討—以美和技術學院為例。大葉學報,13(2),19-37。https://doi.org/10.7119/JDYU.200412.0019
Adler, R., Roberts, H., Crombie, N., & Dixon, K. (2021). Determinants of accounting students’ undergraduate learning satisfaction. Accounting & Finance, 61(4), 5231- 5254. https://doi.org/10.1111/acfi.12756
Afflerbach, P. (Ed.). (2015). Handbook of individual differences in reading: Reader, text, and context. Routledge. https://doi.org/10.4324/9780203075562-18
Agarwal, R., & Prasad, J. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information Systems Research, 9(2), 204-215. https://doi.org/10.1287/isre.9.2.204
Aibinu, I., Odugbemi, T., Koenig, W., & Ghebremedhin, B. (2012). Sequence type ST131 and ST10 complex (ST617) predominant among CTX-M-15-producing Escherichia coli isolates from Nigeria. Clinical Microbiology and Infection, 18(3), E49-E51. https://doi.org/10.1111/j.1469-0691.2011.03730.x
Aizikovitsh-Udi, E., & Amit, M. (2011). Developing the skills of critical and creative thinking by probability teaching. Procedia-Social and Behavioral Sciences, 15, 1087-1091. https://doi.org/10.1016/j.sbspro.2011.03.243
Alhadabi, A., & Karpinski, A. C. (2020). Grit, self-efficacy, achievement orientation goals, and academic performance in University students. International Journal of Adolescence and Youth, 25(1), 519-535. https://doi.org/10.1080/02673843.2019.1679202
Al-Rahmi, W. M., Alias, N., Othman, M. S., Alzahrani, A. I., Alfarraj, O., Saged, A. A., & Rahman, N. S. A. (2018). Use of e-learning by university students in Malaysian higher educational institutions: A case in Universiti Teknologi Malaysia. IEEE Access, 6, 14268-14276. https://doi.org/10.1109/ACCESS.2018.2802325
An, Z., Wang, C., Li, S., Gan, Z., & Li, H. (2021). Technology-assisted self-regulated English language learning: Associations with English language self-efficacy, English enjoyment, and learning outcomes. Frontiers in Psychology, 11, 558466. https://doi.org/10.3389/fpsyg.2020.558466
Anderson, J. R., Corbett, A. T., Koedinger, K. R., & Pelletier, R. (1995). Cognitive tutors: Lessons learned. Journal of Learning Sciences, 4(2), 167-207. https://doi.org/10.1207/s15327809jls0402_2
Anthony, B., Kamaludin, A., Romli, A., Raffei, A. F. M., Nincarean, A., L Eh Phon, D., Abdullah, A., Ming, G. L., Shukor, N. A., Nordin, M. S., & Baba, S. (2019). Exploring the role of blended learning for teaching and learning effectiveness in institutions of higher learning: An empirical investigation. Education and Information Technologies, 24(6), 3433-3466. https://doi.org/10.1007/s10639-019- 09941-z
Anthony, B., Kamaludin, A., Romli, A., Raffei, A. F. M., Nincarean, A., L Eh Phon, D., Abdullah, A., Ming, G. L., Shukor, N. A., Nordin, M. S., & Baba, S. (2019). Exploring the role of blended learning for teaching and learning effectiveness in institutions of higher learning: An empirical investigation. Education and Information Technologies, 24(6), 3433-3466. https://doi.org/10.1007/s10639-019- 09941-z
Athanassopoulos, S., Manoli, P., Gouvi, M., Lavidas, K., & Komis, V. (2023). The use of ChatGPT as a learning tool to improve foreign language writing in a multilingual and multicultural classroom. Advances in Mobile Learning Educational Research, 3(2), 818-824. https://doi.org/10.25082/AMLER.2023.02.009
Bandura, A. (2001). Social cognitive theory: An agentic perspective. Annual Review of Psychology, 52(1), 1-26. https://doi.org/10.1146/annurev.psych.52.1.1
Bandura, A. (2012). On the functional properties of perceived self-efficacy revisited. Journal of Management, 38(1), 9-44. https://doi.org/10.1177/0149206311410606
Bandura, A., Freeman, W. H., & Lightsey, R. (1999). Self-efficacy: The exercise of control. https://doi.org/10.1891/0889-8391.13.2.158
Bartels, J., & Reinders, M. J. (2011). Consumer innovativeness and its correlates: A propositional inventory for future research. Journal of Business Research, 64(6), 601-609. https://doi.org/10.1016/j.jbusres.2010.05.002
Bell, J. H. (1991). Using peer response groups in ESL writing classes. TESL Canada Journal, 8(2), 65-71. https://doi.org/10.18806/tesl.v8i2.589
Bigelow, F.J., Clark, G.M., Lum, J. A.G., & Enticott, P. G. (2021). The mediating effect of language on the development of cognitive and affective theory of mind. Journal of Experimental Child Psychology, 209, 105158. https://doi.org/10.1016/j.jecp.2021.105158
Bowyer, J., & Chambers, L. (2017). Evaluating blended learning: Bringing the elements together. https://doi.org/10.17863/CAM.100355
Broadbent, J., & Poon, W. L. (2015). Self-regulated learning strategies & academic achievement in online higher education learning environments: A systematic review. The Internet and Higher Education, 27, 1-13. https://doi.org/10.1016/j.iheduc.2015.04.007
Bruer, J. T. (1995). Penicillin for education: How cognitive science can contribute to education. NASSP Bulletin, 79(571), 68-80. https://doi.org/10.1177/019263659507957110
Çakici, D. (2018). Metacognitive awareness and critical thinking abilities of pre-service EFL teachers. Journal of Education and Learning, 7(5), 116-129.
Chang, S. H., Wang, C. L., & Lee, J. C. (2016). Do award-winning experiences benefit students' creative self-efficacy and creativity? The moderated mediation effects of perceived school support for creativity. Learning and Individual Differences, 51, 291-298. https://doi.org/10.1016/j.lindif.2016.09.011
Chen, S., & McDunn, B. A. (2022). Metacognition: History, measurements, and the role in early childhood development and education. Learning and Motivation, 78, 101786. https://doi.org/10.1016/j.lmot.2022.101786
Chen, X., Xie, H., & Hwang, G. J. (2020a). A Multi-perspective study on artificial intelligence in education: Grants, conferences, journals, software tools, institutions, and researchers. Computers and Education: Artificial Intelligence, 1, 100005. https://doi.org/10.1016/j.caeai.2020.100005
Chen, X., Xie, H., Zou, D., & Hwang, G. J. (2020b). Application and theory gaps during the rise of Artificial Intelligence in education. Computers and Education: Artificial Intelligence, 1, 100002. https://doi.org/10.1016/j.caeai.2020.100002
Chen, X., Zou, D., Xie, H., Cheng, G., & Liu, C. (2022). Two decades of artificial intelligence in education: Contributors, collaborations, research topics, challenges, and future directions. Educational Technology & Society, 25(1), 28-47. https://doi.org/10.30191/ETS.202201_25(1).0003
Chiang, Y. H., & Hung, K. P. (2014). Team control mode, workers' creativity, and new product innovativeness. R&D Management, 44(2), 124-136. https://doi.org/10.1111/radm.12044
Chiu, T. K., & Hew, T. K. (2018). Factors influencing peer learning and performance in MOOC asynchronous online discussion forum. Australasian Journal of Educational Technology, 34(4). https://doi.org/10.14742/ajet.3240
Cohen, J. (1988). Statistical power analysis for the behavioral science (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum.
Cohen, R. J., & Swerdlik, M. E. (2018). Psychological testing and assessment: An introduction to tests and measurement (9th ed). McGraw-Hill Education.
Creswell, A., White, T., Dumoulin, V., Arulkumaran, K., Sengupta, B., & Bharath, A. A. (2018). Generative adversarial networks: An overview. IEEE Signal Processing Magazine, 35(1), 53-65. https://doi.org/10.1109/MSP.2017.2765202
Dakduk, S., Santalla-Banderali, Z., & Van Der Woude, D. (2018). Acceptance of blended learning in executive education. Sage Open, 8(3), 2158244018800647. https://doi.org/10.1177/2158244018800647
De Jong, J., & Den Hartog, D. (2010). Measuring innovative work behaviour. Creativity and Innovation Management, 19(1), 23-36. https://doi.org/10.1111/j.1467-8691.2010.00547.x
Deng, R., Benckendorff, P., & Gannaway, D. (2019). Progress and new directions for teaching and learning in MOOCs. Computers & Education, 129, 48-60. https://doi.org/10.1016/j.compedu.2018.10.019
Ding, L., & Er, E. (2018). Determinants of college students’ use of online collaborative help‐seeking tools. Journal of Computer Assisted Learning, 34(2), 129-139. https://doi.org/10.1111/jcal.12221
Duffy, M. C., Azevedo, R., Sun, N. Z., Griscom, S. E., Stead, V., Crelinsten, L., ... & Lachapelle, K. (2015). Team regulation in a simulated medical emergency: An in-depth analysis of cognitive, metacognitive, and affective processes. Instructional Science, 43, 401-426. https://doi.org/10.1007/s11251-014-9333-6
Durndell, A., Macleod, H., & Siann, G. (1987). A survey of attitudes to, knowledge about and experience of computers. Computers & Education, 11(3), 167-175. https://doi.org/10.1016/0360-1315(87)90051-0
Efklides, A. (2008). Metacognition: Defining its facets and levels of functioning in relation to self-regulation and co-regulation. European Psychologist, 13(4), 277-287. https://doi.org/10.1027/1016-9040.13.4.277
Escalante, J., Pack, A., & Barrett, A. (2023). AI-generated feedback on writing: insights into efficacy and ENL student preference. International Journal of Educational Technology in Higher Education, 20(1), 57. https://doi.org/10.1186/s41239-023-00425-2
Fang, F., & Tang, X. (2021). The relationship between Chinese English major students’ learning anxiety and enjoyment in an English language classroom: A positive psychology perspective. Frontiers in Psychology, 12, 705244. https://doi.org/10.3389/fpsyg.2021.705244
Fisher, R., Perényi, A., & Birdthistle, N. (2021). The positive relationship between flipped and blended learning and student engagement, performance and satisfaction. Active Learning in Higher Education, 22(2), 97-113. https://doi.org/10.1177/1469787418801702
Fiske, S. T., & Taylor, S. E. (1991). Social cognition (2nd ed.). Mcgraw-Hill Book Company.
Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive–developmental inquiry. American Psychologist, 34(10), 906. https://doi.org/10.1037/0003-066X.34.10.906
Flavell, J. H. (1987). Speculations about the nature and development of meta-cognition. In F. E. Weinert, & R. Kluwe (Eds.), Metacognition, motivation, and understanding (pp. 21-29). Lawrence Erlbaum Associates.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.1177/002224378101800104
Garad, A., Al-Ansi, A. M., & Qamari, I. N. (2021). The role of e-learning infrastructure and cognitive competence in distance learning effectiveness during the COVID-19 pandemic. Jurnal Cakrawala Pendidikan, 40(1), 81-91. https://doi.org/10.21831/cp.v40i1.33474
García-Carrion, B., Munoz-Leiva, F., Del Barrio-García, S., & Porcu, L. (2024). The effect of online message congruence, destination-positioning, and emojis on users’ cognitive effort and affective evaluation. Journal of Destination Marketing & Management, 31, 100842. https://doi.org/10.1016/j.jdmm.2023.100842
Gascoine, L., Higgins, S., & Wall, K. (2017). The assessment of metacognition in children aged 4–16 years: a systematic review. Review of Education, 5(1), 3-57. https://doi.org/10.1016/j.lmot.2022.101786
Gasser, U., & Almeida, V. A. (2017). A layered model for AI governance. IEEE Internet Computing, 21(6), 58-62. https://doi.org/10.1016/j.compedu.2019.02.015
Geoghegan, W. (1994). Whatever happened to instructional technology?. In Paper presented at the 22nd Annual Conference of the International Business Schools Computing Association. https://doi.org/10.1049/et:20080609
Göksün, D. O., & Gürsoy, G. (2019). Comparing success and engagement in gamified learning experiences via Kahoot and Quizizz. Computers & Education, 135, 15-29. https://doi.org/10.1016/j.compedu.2019.02.015
Goldsmith, R. E., & Foxall, G. R. (2003). The measurement of innovativeness. The international handbook on innovation, 5, 321-330. https://doi.org/10.1016/B978-008044198-6/50022-X
Graesser, A. C., Lu, S., Jackson, G. T., Mitchell, H. H., Ventura, M., Olney, A., & Louwerse, M. M. (2004). AutoTutor: A tutor with dialogue in natural language. Behavior Research Methods, Instruments, & Computers, 36, 180-192. https://doi.org/10.3758/BF03195563
Green, S. B., & Salkind, N. J. (2010). Using SPSS for windows and macintosh: analyzing and understanding data. Prentice Hall Press. https://doi.org/10.1198/tas.2005.s139
Habibi, A., Muhaimin, M., Danibao, B. K., Wibowo, Y. G., Wahyuni, S., & Octavia, A. (2023). ChatGPT in higher education learning: Acceptance and use. Computers and Education: Artificial Intelligence, 100190. https://doi.org/10.1007/s40692-022-00244-w
Hair Jr, J. F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. European Business Review, 26(2), 106-121. https://doi.org/10.1016/j.jfbs.2014.01.002
Halpern, D. F. (1998). Teaching critical thinking for transfer across domains: Disposition, skills, structure training, and metacognitive monitoring. American Psychologist, 53(4), 449. https://doi.org/10.1037/0003-066X.53.4.449
Hansen, J.,&Liu, J. (2005). Guiding principles for effective peer response. ELT Journal, 59, 31–38. https://doi.org/10.1093/elt/cci004
Hargrove, R. A., & Nietfeld, J. L. (2015). The impact of metacognitive instruction on creative problem solving. The Journal of Experimental Education, 83(3), 291-318. https://doi.org/10.1080/00220973.2013.876604
Haynes, B. (2020). Can creativity be taught?. Educational Philosophy and Theory, 52(1), 34-44. https://doi.org/10.1080/00131857.2019.1594194
Heffernan, N. T., & Heffernan, C. L. (2014). The ASSISTments ecosystem: Building a platform that brings scientists and teachers together for minimally invasive research on human learning and teaching. International Journal of Artificial Intelligence in Education, 24, 470-497. https://doi.org/10.1007/s40593-014-0024-x
Hidayati, T., & Diana, S. (2019). Students’ motivation to learn English using mobile applications: The case of Duolingo and Hello English. JEELS (Journal of English Education and Linguistics Studies), 6(2), 189-213. https://doi.org/10.30762/jeels.v6i2.1233
Ho, W. Y. (2017). A review of blended synchronous learning. International Journal of Social Media and Interactive Learning Environments, 5(4), 278-291. https://doi.org/10.1504/IJSMILE.2017.090977
Hong, J. C., Cao, W., Liu, X., Tai, K. H., & Zhao, L. (2023). Personality traits predict the effects of Internet and academic self-efficacy on practical performance anxiety in online learning under the COVID-19 lockdown. Journal of Research on Technology in Education, 55(3), 426-440. https://doi.org/10.1080/15391523.2021.1967818
Hong, J. C., Hwang, M. Y., Hsu, H. T., & Tai, K. H. (2021). Gestalt perception: A game designed to explore players’ gameplay self-efficacy and anxiety reflected in their learning effects. Journal of Research on Technology in Education, 441-458. https://doi.org/10.1080/15391523.2021.1967819
Hong, J. C., Hwang, M. Y., Tai, K. H., & Kuo, Y. C. (2016). Crystallized intelligence affects hedonic and epistemic values to continue playing a game with saliency-based design. Computers & Education, 95, 75-84. https://doi.org/10.1016/j.compedu.2015.12.006
Hong, J. C., Lin, P. H., & Hsieh, P. C. (2017). The effect of consumer innovativeness on perceived value and continuance intention to use smartwatch. Computers in Human Behavior, 67, 264-272. https://doi.org/10.1016/j.compedu.2018.10.019
Hong, J.-C., Liu, X., Cao, W., Tai, K.-H., & Zhao, L. (2022). Effects of self-efficacy and online learning mind states on learning ineffectiveness during the COVID-19 lockdown. Educational Technology & Society, 25(1), 142–154. https://www.jstor.org/stable/48647036
Huang, T. C., Chen, C. C., & Chou, Y. W. (2016). Animating eco-education: To see, feel, and discover in an augmented reality-based experiential learning environment. Computers & Education, 96, 72-82.
https://doi.org/10.1016/j.compedu.2016.02.008
Huang, X., Bernacki, M. L., Kim, D., & Hong, W. (2022). Examining the role of self-efficacy and online metacognitive monitoring behaviors in undergraduate life science education. Learning and Instruction, 80, 101577. https://doi.org/10.1016/j.learninstruc.2021.101577
Huang, Y. M. (2019). Examining students' continued use of desktop services: Perspectives from expectation-confirmation and social influence. Computers in Human Behavior, 96, 23-31. https://doi.org/10.1016/j.chb.2019.02.010
Hung, I. C., Yang, X. J., Fang, W. C., Hwang, G. J., & Chen, N. S. (2014). A Context-aware video prompt approach to improving students’ in-field reflection levels. Computers & Education, 70, 80–91. https://doi.org/10.1016/j.compedu.2013.08.007
Hwang, G. J., & Chang, C. Y. (2023). A review of opportunities and challenges of chatbots in education. Interactive Learning Environments, 31(7), 4099–4112. https://doi.org/10.1080/10494820.2021.1952615
Hwang, G. J., Hung, P. H., Chen, N. S. & Liu, G.Z. (2014). Mindtool-assisted in-field learning (MAIL): An advanced ubiquitous learning project in Taiwan. Journal of Educational Technology & Society, 17(2), 4–16. http://www.jstor.org/stable/jeductechsoci.17.2.4
Hwang, G. J., Wu, P. H., & Ke, H. R. (2011). An interactive concept map approach to supporting mobile learning activities for natural science courses. Computers & Education, 57(4), 2272-2280. https://doi.org/10.1016/j.compedu.2011.06.011
Hwang, G.-J., Xie, H., Wah, B., & Gašević, D. (2020). Vision, challenges, roles and research issues of Artificial Intelligence in Education. Computers and Education: Artificial Intelligence, 1, 100001. https://doi.org/10.1016/j.caeai.2020.100001
Igbaria, M., & Iivari, J. (1995). The effects of self-efficacy on computer usage. Omega, 23(6), 587-605. https://doi.org/10.1016/0305-0483(95)00035-6
Imran, M., & Almusharraf, N. (2023). Analyzing the role of ChatGPT as a writing assistant at higher education level: A systematic review of the literature. Contemporary Educational Technology, 15(4), ep464. https://doi.org/10.30935/cedtech/13605
Jansen, M. A., & Franz, N. M. (2015). Phylogenetic revision of Minyomerus Horn, 1876 sec. Jansen & Franz, 2015 (Coleoptera, Curculionidae) using taxonomic concept annotations and alignments. ZooKeys, 528, 1. https://doi.org/10.3897/zookeys.528.6001
Jiang, S., Wang, J., Zhang, R., & Liu, O. (2023). Innovation climate for individual motivation and innovation performance: Is innovative behavior a missing link? Journal of Innovation & Knowledge, 8, 100440. https://doi.org/10.1016/j.jik.2023.100440
Jiang, Y., Ma, L., & Gao, L. (2016). Assessing teachers' metacognition in teaching: The teacher metacognition inventory. Teaching and Teacher Education, 59, 403-413. https://doi.org/10.1016/j.tate.2016.07.014
Kang, D., & Park, M. J. (2023). Learner innovativeness, course interaction, and the use of a new educational technology system after the COVID-19 pandemic. The International Journal of Management Education, 100824. https://doi.org/10.1016/j.ijme.2023.100824
Kilicer, K., Bardakci, S., & Arpaci, I. (2018). Investigation of emerging technology usage characteristics as predictors of innovativeness. Contemporary Educational Technology, 9(3), 225-245. https://doi.org/10.30935/cet.444100
Kim, E. J., Kim, J. J., & Han, S. H. (2021). Understanding student acceptance of online learning systems in higher education: Application of social psychology theories with consideration of user innovativeness. Sustainability, 13(2), 896. https://doi.org/10.3390/su13020896
Kim, J., Merrill, K., Xu, K., & Sellnow, D. D. (2020). My teacher is a machine: Understanding students’ perceptions of AI teaching assistants in online education. International Journal of Human–Computer Interaction, 36(20), 1902-1911. https://doi.org/10.1080/10447318.2020.1801227
Kirkpatrick, J. D., & Kirkpatrick, W. K. (2016). Kirkpatrick's four levels of training evaluation. Association for Talent Development.
Kline, P. (2013). Handbook of psychological testing. Routledge.
Korbicz, J., Koscielny, J. M., Kowalczuk, Z., & Cholewa, W. (Eds.). (2012). Fault diagnosis: Models, artificial intelligence, applications. Springer Science & Business Media.
Kuhn, D. (1999). A developmental model of critical thinking. Educational Researcher, 28(2), 16-46. https://doi.org/10.3102/0013189X028002016
Kuvac, M., & Koc, I. (2019). The effect of problem-based learning on the environmental attitudes of preservice science teachers. Educational Studies, 45(1), 72-94. https://doi.org/10.1080/03055698.2018.1443795
Lakin, J. L., Chartrand, T. L., & Arkin, R. M. (2008). I am too just like you: Nonconscious mimicry as an automatic behavioral response to social exclusion. Psychological Science, 19(8), 816-822. https://doi.org/10.1111/j.1467-9280.2008.02162.x
Lam, R., & Moorhouse, B. L. (2022). Using digital portfolios to develop students’ writing: A practical guide for language teachers. Taylor & Francis. https://doi.org/10.4324/9781003295860-6
Lamb, S., & Kwok, K. C. (2019). The effects of motion sickness and sopite syndrome on office workers in an 18-month field study of tall buildings. Journal of Wind Engineering and Industrial Aerodynamics, 186, 105-122. https://doi.org/10.1016/j.jweia.2019.01.004
Lau, R. S., & Cheung, G. W. (2012). Estimating and comparing specific mediation effects in complex latent variable models. Organizational Research Methods, 15(1), 3-16. https://doi.org/10.1177/1094428110391673
Lee, S. C., IrvIng, K., Pape, S., & Owens, D. (2015). Teachers’ use of interactive technology to enhance students’ metacognition: Awareness of student learning and feedback. Journal of Computers in Mathematics and Science Teaching, 34(2), 175-198.
Lin, C. H., Yu, C. C., Shih, P. K., & Wu, L. Y. (2021). STEM-based artificial intelligence learning in general education for non-engineering undergraduate students. Educational Technology & Society, 24(3), 224-237. https://doi.org/10.30191/ETS.202107_24(3).0016
Liu, Y. C., Wang, W. T., & Lee, T. L. (2021). An integrated view of information feedback, game quality, and autonomous motivation for evaluating game-based learning effectiveness. Journal of Educational Computing Research, 59(1), 3-40. https://doi.org/10.1177/0735633120952044
Lund, B. D., & Wang, T. (2023). Chatting about ChatGPT: How may AI and GPT impact academia and libraries? Library Hi Tech News, 40(3), 26-29. https://doi.org/10.1108/LHTN-01-2023-0009
Lundstrom, K., & Baker, W. (2009). To give is better than to receive: The benefits of peer review to the reviewer's own writing. Journal of Second Language Writing, 18(1), 30-43. https://doi.org/10.1016/j.jslw.2008.06.002
Ma, W., Adesope, O. O., Nesbit, J. C., & Liu, Q. (2014). Intelligent tutoring systems and learning outcomes: A meta-analysis. Journal of Educational Psychology, 106(4), 901. https://doi.org/10.1037/a0037123.supp
Macfadyen, L. P., Dawson, S., Pardo, A., & Gaševic, D. (2014). Embracing big data in complex educational systems: The learning analytics imperative and the policy challenge. Research & Practice in Assessment, 9, 17-28.
MacKinnon, D. (2012). Introduction to statistical mediation analysis. Routledge.
Magno, C. (2010). The role of metacognitive skills in developing critical thinking. Metacognition and Learning, 5, 137-156. https://doi.org/10.1007/s11409-010-9054-4
Mahat, J., Ayub, A. F. M., & Luan, S. (2012). An assessment of students’ mobile self-efficacy, readiness and personal innovativeness towards mobile learning in higher education in Malaysia. Procedia-Social and Behavioral Sciences, 64, 284-290. https://doi.org/10.1016/j.sbspro.2012.11.033
Maor, R., Paz-Baruch, N., Grinshpan, N., Milman, A., Mevarech, Z., Levi, R., ... & Zion, M. (2023). Relationships between metacognition, creativity, and critical thinking in self-reported teaching performances in project-based learning settings. Thinking Skills and Creativity, 50, 101425. https://doi.org/10.1016/j.tsc.2023.101425
Marcoulides, K. M., & Raykov, T. (2019). Evaluation of variance inflation factors in regression models using latent variable modeling methods. Educational and Psychological Measurement, 79(5), 874-882. https://doi.org/10.1177/0013164418817803
Marin, L. M., & Halpern, D. F. (2011). Pedagogy for developing critical thinking in adolescents: Explicit instruction produces greatest gains. Thinking Skills and Creativity, 6(1), 1-13. https://doi.org/10.1016/j.tsc.2010.08.002
Martelletti, D. M., Luzuriaga, M., & Furman, M. (2023). ‘What makes you say so?’Metacognition improves the sustained learning of inferential reading skills in English as a second language. Trends in Neuroscience and Education, 100213. https://doi.org/10.1016/j.tine.2023.100213
Martelletti, D. M., Luzuriaga, M., & Furman, M. (2023). ‘What makes you say so?’ Metacognition improves the sustained learning of inferential reading skills in English as a second language. Trends in Neuroscience and Education, 33, 100213. https://doi.org/10.1016/j.tine.2023.100213
Marzuki, Widiati, U., Rusdin, D., Darwin, & Indrawati, I. (2023). The impact of AI writing tools on the content and organization of students’ writing: EFL teachers’ perspective. Cogent Education, 10(2), 2236469. https://doi.org/10.1080/2331186X.2023.2236469
Mayer, R. E. (Ed.). (2014). The Cambridge handbook of multimedia learning (2nd ed.). Cambridge University Press.
McDonald, T., & Siegall, M. (1996). Enhancing worker self‐efficacy: An approach for reducing negative reactions to technological change. Journal of Managerial Psychology, 11(2), 41-44. https://doi.org/10.1108/02683949610110550
McGuire, S., McGuire, S. Y., & Angelo, T. (2015). Teach students how to learn: Strategies you can incorporate into any course to improve student metacognition, study skills, and motivation. Routledge.
McMurry, A. I. (2005). Preparing students for peer review. Brigham Young University.
Messmann, G., & Mulder, R. H. (2015). Reflection as a facilitator of teachers' innovative work behaviour. International Journal of Training and Development, 19(2), 125-137. https://doi.org/10.1111/ijtd.12052
Mhlanga, D. (2023). Open AI in education, the responsible and ethical use of ChatGPT towards lifelong learning. Education, the Responsible and Ethical Use of ChatGPT Towards Lifelong Learning (February 11, 2023).
Midgley, D. F., & Dowling, G. R. (1978). Innovativeness: The concept and its measurement. Journal of Consumer Research, 4(4), 229-242. https://doi.org/10.1086/208701
Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017-1054. https://doi.org/10.1111/j.1467-9620.2006.00684.x
Mogavi, R. H., Deng, C., Kim, J. J., Zhou, P., Kwon, Y. D., Metwally, A. H. S., ... & Hui, P. (2024). ChatGPT in education: A blessing or a curse? A qualitative study exploring early adopters’ utilization and perceptions. Computers in Human Behavior: Artificial Humans, 2(1), 100027. https://doi.org/10.1016/j.chbah.2023.100027
Muis, K. R., Chevrier, M., & Singh, C. A. (2018). The role of epistemic emotions in personal epistemology and self-regulated learning. Educational Psychologist, 53(3), 165-184. https://doi.org/10.1080/00461520.2017.1421465
Müller, F. A., & Wulf, T. (2020). Technology-supported management education: a systematic review of antecedents of learning effectiveness. International Journal of Educational Technology in Higher Education, 17, 1-33. https://doi.org/10.1186/s41239-020-00226-x
Müller, F. A., & Wulf, T. (2020). Technology-supported management education: a systematic review of antecedents of learning effectiveness. International Journal of Educational Technology in Higher Education, 17(1), 1-33. https://doi.org/10.1186/s41239-020-00226-x
Namaziandost, E., & Çakmak, F. (2020). An account of EFL learners’ self-efficacy and gender in the Flipped Classroom Model. Education and Information Technologies, 25(5), 4041-4055. https://doi.org/10.1007/s10639-020-10167-7
Ngafeeson, M. N., & Sun, J. (2015). The effects of technology innovativeness and system exposure on student acceptance of e-textbooks. Journal of Information Technology Education: Research, 14, 55. https://doi.org/10.28945/2101
Nichols, J. A., Herbert Chan, H. W., & Baker, M. A. (2019). Machine learning: applications of artificial intelligence to imaging and diagnosis. Biophysical Reviews, 11, 111-118. https://doi.org/10.1007/s12551-018-0449-9
Niels Bonderup Dohn & Nina Bonderup Dohn (2017). Integrating Facebook in upper secondary biology instruction: a case study of students’ situational interest and participation in learning communication. Research in Science Education, 47, 1305-1329. https://doi.org/10.1007/s11165-016-9549-3
OECD., K. (2018). OECD science, technology and innovation outlook 2018. OECD publishing. https://doi.org/10.1787/25186167
Orlov, G., McKee, D., Berry, J., Boyle, A., DiCiccio, T., Ransom, T., & Stoye, J. (2021). Learning during the COVID-19 pandemic: It is not who you teach, but how you teach. Economics Letters, 202, 109812. https://doi.org/10.1016/j.econlet.2021.109812
Pajares, F. (1996). Self-efficacy beliefs in academic settings. Review of Educational Research, 66(4), 543-578. https://doi.org/10.3102/00346543066004543
Pihlström, M., & Brush, G. J. (2008). Comparing the perceived value of information and entertainment mobile services. Psychology & Marketing, 25(8), 732-755. https://doi.org/10.1002/mar.20236
Poon, W. C., Kunchamboo, V., & Koay, K. Y. (2022). E-learning engagement and effectiveness during the COVID-19 pandemic: The interaction model. International Journal of Human–Computer Interaction, 1-15. https://doi.org/10.1080/10447318.2022.2119659
Prasad, P. W. C., Maag, A., Redestowicz, M., & Hoe, L. S. (2018). Unfamiliar technology: Reaction of international students to blended learning. Computers & Education, 122, 92-103. https://doi.org/10.1016/j.compedu.2018.03.016
Raphael, T. E., Kirschner, B. W., & Englert, C. S. (1988). Expository writing program: Making connections between reading and writing. The Reading Teacher, 41(8), 790–795. http://www.jstor.org/stable/20199924
Rasheed, R. A., Kamsin, A., & Abdullah, N. A. (2020). Challenges in the online component of blended learning: A systematic review. Computers & Education, 144, 103701. https://doi.org/10.1016/j.compedu.2019.103701
Roblyer, M., & Doering, A. H. (2007). Integrating educational technology into teaching. Pearson, 2007.
Rogers, E. M. (2003). Diffusion of innovations. Free Press. https://doi.org/10.4000/essais.11135
Rogers, E. M., & Shoemaker, F. F. (1971). Communication of Innovations: A cross-cultural approach. https://doi.org/10.2307/2800105
Rollinson, P. (2005). Using peer feedback in the ESL writing class. ELT Journal, 59(1), 23-30. https://doi.org/10.1093/elt/cci003
Russell, S. J., & Norvig, P. (2016). Artificial intelligence: a modern approach. Pearson.
Sari, R., & Karsen, M. (2016, November). An empirical study on blended learning to improve quality of learning in higher education. In 2016 International conference on information management and technology (ICIMTech) (pp. 235-240). IEEE. https://doi.org/10.1109/ICIMTech.2016.7930336
Sarwar, H., Akhtar, H., Naeem, M. M., Khan, J. A., Waraich, K., Shabbir, S., Hasan A., & Khurshid, Z. (2020). Self-reported effectiveness of e-Learning classes during COVID-19 pandemic: A nation-wide survey of Pakistani undergraduate dentistry students. European Journal of Dentistry, 14(S01), S34-S43.https://doi.org/10.1055/s-0040-1717000
Savara, V., & Parahoo, S. (2018). Unraveling determinants of quality in blended learning: Are there gender-based differences? International Journal of Quality & Reliability Management, 35(9), 2035-2051. https://doi.org/10.1108/IJQRM-11-2017-0233
Schraw, G., & Dennison, R. S. (1994). Assessing metacognitive awareness. Contemporary Educational Psychology, 19(4), 460-475. https://doi.org/10.1006/ceps.1994.1033
Schraw, G., & Moshman, D. (1995). Metacognitive theories. Educational Psychology Review, 7, 351-371. https://doi.org/10.1007/BF02212307
Schraw, G., Crippen, K. J., & Hartley, K. (2006). Promoting self-regulation in science education: Metacognition as part of a broader perspective on learning. Research in Science Education, 36, 111-139. https://doi.org/10.1007/s11165-005-3917-8
Schunk, D. H., & DiBenedetto, M. K. (2021). Self-efficacy and human motivation. In Advances in motivation science (Vol. 8, pp. 153-179). Elsevier. https://doi.org/10.1016/bs.adms.2020.10.001
Schunk, D. H., & Usher, E. L. (2012). Social cognitive theory and motivation. In R. M. Ryan (Ed.), The Oxford handbook of human motivation (2ed., pp, 11-26). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780195399820.013.0002
Searle, J. R. (1980). Minds, brains, and programs. Behavioral and Brain Sciences, 3(3), 417-424. https://doi.org/10.1093/oxfordhb/9780195399820.013.0002
Searle, J. R. (2008). Mind, language and society: Philosophy in the real world. Basic books.
Shakroum, M., Wong, K. W., & Fung, C. C. (2018). The influence of gesture-based learning system (GBLS) on learning outcomes. Computers & Education, 117, 75- 101. https://doi.org/10.1016/j.compedu.2017.10.002
Siburian, J., Corebima, A. D., & Saptasari, M. (2019). The correlation between critical and creative thinking skills on cognitive learning results. Eurasian Journal of Educational Research, 19(81), 99-114. https://doi.org/10.14689/ejer.2019.81.6
Siemens, G., Dawson, S., & Lynch, G. (2013). Improving the quality and productivity of the higher `ucation sector. Policy and Strategy for Systems-Level Deployment of Learning Analytics. Canberra, Australia: Society for Learning Analytics Research for the Australian Office for Learning and Teaching, 31.
Steenbergen-Hu, S., & Cooper, H. (2014). A meta-analysis of the effectiveness of intelligent tutoring systems on college students’ academic learning. Journal of Educational Psychology, 106(2), 331. https://doi.org/10.1037/a0034752
Stevenson, A. (Ed.). (2010). Oxford dictionary of English. Oxford University Press, USA. https://doi.org/10.1093/acref/9780199571123.001.0001
Sun, Y., Hong, J. C., & Ye, J. H. (2022). The effects of employees’ perceived intrinsic motivation on knowledge sharing and creative self-efficacy. Frontiers in Psychology, 12, 762994. https://doi.org/10.3389/fpsyg.2021.762994
Sung, Y. T., Chang, K. E., & Liu, T. C. (2016). The effects of integrating mobile devices with teaching and learning on students' learning performance: A meta-analysis and research synthesis. Computers & Education, 94, 252-275. https://doi.org/10.1016/j.compedu.2015.11.008
Tidd, J., & Bessant, J. (2018). Innovation management challenges: From fads to fundamentals. International Journal of Innovation Management, 22(5), 1840007. https://doi.org/10.1142/S1363919618400078
To, C. K., Martinez, J. M. G., Orero-Blat, M., & Chau, K. P. (2020). Predicting motivational outcomes in social entrepreneurship: Roles of entrepreneurial self-efficacy and situational fit. Journal of Business Research, 121, 209-222. https://doi.org/10.1016/j.jbusres.2020.08.022
Tseng, H., Kuo, Y. C., & Walsh, E. J. (2020). Exploring first-time online undergraduate and graduate students’ growth mindsets and flexible thinking and their relations to online learning engagement. Educational Technology Research and Development, 68(5), 2285-2303. https://doi.org/10.1007/s11423-020-09774-5
Ülger, K. (2016). The relationship between creative thinking and critical thinking skills of students. Hacettepe Universitesi Egitim Fakultesi Dergisi-Hacettepe University Journal of Education, 31. https://doi.org/10.16986/huje.2016018493
Usher, E. L., & Pajares, F. (2008). Sources of self-efficacy in school: Critical review of the literature and future directions. Review of Educational Research, 78(4), 751-796. https://doi.org/10.3102/0034654308321456
Usher, E. L., & Schunk, D. H. (2017). Social cognitive theoretical perspective of self-regulation. In Handbook of self-regulation of learning and performance (pp. 19-35). Routledge. https://doi.org/10.4324/9781315697048-2
VanLehn, K. (2011). The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems. Educational Psychologist, 46(4), 197-221. https://doi.org/10.1080/00461520.2011.611369
Veenman, M. V. (2013). Assessing metacognitive skills in computerized learning environments. In R. Azevedo & V. Aleven (Eds.), International handbook of metacognition and learning technologies (pp. 157-168). Springer New York. https://doi.org/10.1007/978-1-4419-5546-3_11
Victori, M., & Lockhart, W. (1995). Enhancing metacognition in self-directed language learning. System, 23(2), 223-234. https://doi.org/10.1016/0346-251X(95)00010-H
Vidergor, H. E. (2023). The effect of teachers' self-innovativeness on accountability, distance learning self-efficacy, and teaching practices. Computers & Education, 199, 104777. https://doi.org/10.1016/j.compedu.2023.104777
Villamil, O. S., & de Guerrero, M. C. M. (1996). Peer revision in the L2 classroom: Social-cognitive activities, mediating strategies, and aspects of social behavior. Journal of Second Language Writing, 5, 51–75. https://doi.org/10.1016/S1060-3743(96)90015-6
Vygotsky, L. S., & Cole, M. (1978). Mind in society: Development of higher psychological processes. Harvard University Press. https://doi.org/10.2307/1421493
Wang, C. H., Shannon, D. M., & Ross, M. E. (2013). Students’ characteristics, self-regulated learning, technology self-efficacy, and course outcomes in online learning. Distance Education, 34(3), 302-323. https://doi.org/10.1080/01587919.2013.835779
Wang, L. H., Chen, B., Hwang, G. J., Guan, J. Q., & Wang, Y. Q. (2022). Effects of digital game-based STEM education on students’ learning achievement: A meta-analysis. International Journal of STEM Education, 9(1), 1-13. https://doi.org/10.1186/s40594-022-00344-0
Wang, Y., Liu, C., & Tu, Y. F. (2021). Factors affecting the adoption of AI-based applications in higher education. Educational Technology & Society, 24(3), 116-129. https://doi.org/10.1016/j.techsoc.2021.101694
Worthington, R. L., & Whittaker, T. A. (2006). Scale development research: A content analysis and recommendations for best practices. The Counseling Psychologist, 34(6), 806-838. https://doi.org/10.1177/0011000006288127
Yashin-Shaw, I. (2003). Developing creativity. In J. C. Stevenson (Ed.), Developing vocational expertise (pp. 153-182). Routledge. https://doi.org/10.4324/9781003115342-9
Yi, M.Y., & Hwang, Y. (2003) Predicting the use of web-based information systems: Self-efficacy, enjoyment, learning goal orientation, and the technology acceptance model. International Journal of Human Computer Studies, 59, 431-449. http://dx.doi.org/10.1016/S1071-5819(03)00114-9
Yilmaz, O., & Bayraktar, D. M. (2014). Teachers’ attitudes towards the use of educational technologies and their individual innovativeness categories. Procedia-Social and Behavioral Sciences, 116, 3458-3461. https://doi.org/10.1016/j.sbspro.2014.01.783
Yuan, F., & Woodman, R. W. (2021). The multiple ways of behaving creatively in the workplace: A typology and model. Journal of Organizational Behavior, 42(1), 20-33. https://doi.org/10.1002/job.2488
Zainudin, A. (2015). SEM made simple: A gentle approach to learning structural equation modeling. MPWS Rich Publication Sdn. Bhd. https://doi.org/10.1134/S0006350918020100
Zhao, Y., Pugh, K., Sheldon, S., & Byers, J. L. (2002). Conditions for classroom technology innovations. Teachers College Record, 104(3), 482-515. https://doi.org/10.1111/1467-9620.00170
Zimmerman, B. J., & Schunk, D. H. (2011). Motivational sources and outcomes of self-regulated learning and performance. Handbook of Self-Regulation of Learning and Performance, 5(3), 49-64. https://doi.org/10.4324/9780203839010.ch4