Abe, E. N., & Chikoko, V. (2020). Exploring the factors that influence the career decision of STEM students at a university in South Africa. International Journal of STEM Education, 7(1), 60. https://doi.org/10.1186/s40594-020-00256-x
Article
Google Scholar
Adukaite, A., van Zyl, I., Er, Ş, & Cantoni, L. (2017). Teacher perceptions on the use of digital gamified learning in tourism education: The case of South African secondary schools. Computers & Education, 111, 172–190. https://doi.org/10.1016/j.compedu.2017.04.008
Article
Google Scholar
Apedoe, X. S., Reynolds, B., Ellefson, M. R., & Schunn, C. D. (2008). Bringing Engineering Design into High School Science Classrooms: The Heating/Cooling Unit. Journal of Science Education and Technology, 17(5), 454–465. https://doi.org/10.1007/s10956-008-9114-6.
Article
Google Scholar
Ariyanto, S., Munoto, M., & Muhaji, M. (2019). Development of Psychomotor Domain Assessment Instrument on Brake System Competence in SMKN 1 Jetis Mojokerto. International Journal for Educational and Vocational Studies. https://doi.org/10.29103/ijevs.v1i6.1648.
Article
Google Scholar
Badri, M., Alnuaimi, A., Mohaidat, J., Al Rashedi, A., Yang, G., & Al Mazroui, K. (2016). My science class and expected career choices—a structural equation model of determinants involving Abu Dhabi high school students. International Journal of STEM Education, 3(1), 12. https://doi.org/10.1186/s40594-016-0045-0.
Article
Google Scholar
Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173–1182. https://doi.org/10.1037/0022-3514.51.6.1173.
Article
Google Scholar
Barrett, A., Pack, A., Guo, Y., & Wang, N. (2020). Technology acceptance model and multi-user virtual reality learning environments for Chinese language education. Interactive Learning Environments. https://doi.org/10.1080/10494820.2020.1855209
Article
Google Scholar
Barrett, A. J., Pack, A., & Quaid, E. D. (2021). Understanding learners’ acceptance of high-immersion virtual reality systems: Insights from confirmatory and exploratory PLS-SEM analyses. Computers & Education, 169, 104214. https://doi.org/10.1016/j.compedu.2021.104214
Article
Google Scholar
Bassachs, M., Cañabate, D., Nogué, L., Serra, T., Bubnys, R., & Colomer, J. (2020). Fostering Critical Reflection in Primary Education through STEAM Approaches. Education Sciences, 10(12), 384. https://www.mdpi.com/2227-7102/10/12/384
Bloom, B. S. (1956). Taxonomy of educational objectives, handbook I: The cognitive domain. David McKay Co Inc.
Google Scholar
Chang, Y.-S., Kuo Jui, H., Chiang, C.-W., & Lugmayr, A. (2019). Applying Mobile Augmented Reality (AR) to Teach Interior Design Students in Layout Plans: Evaluation of Learning Effectiveness Based on the ARCS Model of Learning Motivation Theory. Sensors, 20, 105. https://doi.org/10.3390/s20010105.
Article
Google Scholar
Cheng, K.-H. (2017). Reading an augmented reality book: An exploration of learners’ cognitive load, motivation, and attitudes. Australasian Journal of Educational Technology, 33(4). https://doi.org/10.14742/ajet.2820.
Article
Google Scholar
Chen, C.-C., & Huang, P.-H. (2020). The effects of STEAM-based mobile learning on learning achievement and cognitive load. Interactive Learning Environments. https://doi.org/10.1080/10494820.2020.1761838
Article
Google Scholar
Chu, H.-E., Martin, S. N., & Park, J. (2019). A Theoretical Framework for Developing an Intercultural STEAM Program for Australian and Korean Students to Enhance Science Teaching and Learning. International Journal of Science and Mathematics Education, 17(7), 1251–1266. https://doi.org/10.1007/s10763-018-9922-y
Article
Google Scholar
Conradty, C., & Bogner, F. X. (2020). STEAM teaching professional development works: effects on students’ creativity and motivation. Smart Learning Environments, 7(1), 26. https://doi.org/10.1186/s40561-020-00132-9
Article
Google Scholar
Costley, J., & Lange, C. (2017). The Mediating Effects of Germane Cognitive Load on the Relationship Between Instructional Design and Students’ Future Behavioral Intention. The Electronic Journal of e-Learning, 15(2)
Curran, V., Gustafson, D. L., Simmons, K., Lannon, H., Wang, C., Garmsiri, M., et al. (2019). Adult learners’ perceptions of self-directed learning and digital technology usage in continuing professional education: An update for the digital age. Journal of Adult and Continuing Education, 25(1), 74–93. https://doi.org/10.1177/1477971419827318.
Article
Google Scholar
Dai, H. M., Teo, T., Rappa, N. A., & Huang, F. (2020). Explaining Chinese university students’ continuance learning intention in the MOOC setting: A modified expectation confirmation model perspective. Computers & Education, 150, https://doi.org/10.1016/j.compedu.2020.103850.
Article
Google Scholar
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
Article
Google Scholar
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003.
Article
Google Scholar
Dörnyei, Z., & Taguchi, T. (2009). Questionnaires in Second Language Research: Construction, Administration, and Processing (2nd ed.). Routledge. https://doi.org/10.4324/9780203864739.
Dunn, T. J., & Kennedy, M. (2019). Technology Enhanced Learning in higher education; motivations, engagement and academic achievement. Computers & Education, 137, 104–113. https://doi.org/10.1016/j.compedu.2019.04.004.
Article
Google Scholar
Ekatushabe, M., Kwarikunda, D., Muwonge, C. M., Ssenyonga, J., & Schiefele, U. (2021). Relations between perceived teacher’s autonomy support, cognitive appraisals and boredom in physics learning among lower secondary school students. International Journal of STEM Education, 8(1), 8. https://doi.org/10.1186/s40594-021-00272-5
Article
Google Scholar
Findik-Coşkunçay, D., Alkiş, N., & Özkan-Yildirim, S. (2018). A structural model for students’ adoption of learning management systems: An empirical investigation in the higher education context. Journal of Educational Technology & Society, 21(2), 13–27.
Google Scholar
Fletcher, J. D. (2018). Comments and reflections on ITS and STEM education and training. InternationalJournal of STEM Education, 5(1), 16. https://doi.org/10.1186/s40594-018-0106-7.
Article
Google Scholar
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
Article
Google Scholar
Fu, S., Gu, H., & Yang, B. (2020). The affordances of AI-enabled automatic scoring applications on learners’ continuous learning intention: An empirical study in China. British Journal of Educational Technology,. https://doi.org/10.1111/bjet.12995.
Article
Google Scholar
Galbis-Córdoba, A., Martí-Parreño, J., & Currás-Pérez, R. (2017). Education Students’ Attitude towards the Use of Gamification for Competencies Development. Journal of E-Learning and Knowledge Society, 13, 1. https://doi.org/10.20368/1971-8829/158
Article
Google Scholar
Galeazzo, A., Ortiz-de-Mandojana, N., & Delgado-Ceballos, J. (2021). Green procurement and financial performance in the tourism industry: the moderating role of tourists’ green purchasing behaviour. Current Issues in Tourism, 24(5), 700–716. https://doi.org/10.1080/13683500.2020.1734546
Article
Google Scholar
Gao, X., Li, P., Shen, J., & Sun, H. (2020). Reviewing assessment of student learning in interdisciplinary STEM education. International Journal of STEM Education, 7(1), 24. https://doi.org/10.1186/s40594-020-00225-4.
Article
Google Scholar
Granić, A., & Marangunić, N. (2019). Technology acceptance model in educational context: A systematic literature review. British Journal of Educational Technology, 50(5), 2572–2593. https://doi.org/10.1111/bjet.12864
Article
Google Scholar
Gülen, S., & Yaman S. (2019). The Effect of Integration of STEM Disciplines into Toulmin's Argumentation Model on Students' Academic Achievement, Reflective Thinking, and Psychomotor Skills*. https://doi.org/10.12973/tused.10276.
Gülhan, F., & Şahin, F. (2018, 08/05). The effects of STEAM (STEM+ Art) activities 7th grade students’ academic achievement, STEAM attitude and scientific creativities<p>STEAM (STEM+Sanat) etkinliklerinin 7. sınıf öğrencilerinin akademik başarı, STEAM tutum ve bilimsel yaratıcılıklarına etkisi. Journal of Human Sciences, 15(3), 1675–1699. https://j-humansciences.com/ojs/index.php/IJHS/article/view/5430
Gyamfi, S. A. (2017). Informal Tools in Formal Context: Adoption of Web 2.0 Technologies among Geography Student Teachers in Ghana. International Journal of Education and Development Using Information and Communication Technology, 13(3), 24–40.
Google Scholar
Hair, J. F., Hult, G. T. M., Ringe, C. M., & Sarstedt, M. (2016). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). SAGE Publications.
Hair, J., Black, W., Babin, B., Anderson, R., & Tatham, R. (2006). Multivariate data analysis. Upper Saddle River, NJ: Pearson Prentice Hall.
Google Scholar
Haji, S. A., Moluayonge, G. E., & Park, I. (2017). Teachers’ use of information and communications technology in education: Cameroon secondary schools perspectives. Turkish Online Journal of Educational Technology-TOJET, 16(3), 147–153.
Google Scholar
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
Article
Google Scholar
Horng, J.-S., Liu, C.-H., Chou, S.-F., & Huang, Y.-C. (2020). The roles of university education in promoting students’ passion for learning, knowledge management and entrepreneurialism. Journal of Hospitality and Tourism Management, 44, 162–170. https://doi.org/10.1016/j.jhtm.2020.06.005
Article
Google Scholar
Huang, W., Huang, W., Diefes-Dux, H., & Imbrie, P. K. (2006). A preliminary validation of Attention, Relevance, Confidence and Satisfaction model-based Instructional Material Motivational Survey in a computer-based tutorial setting. British Journal of Educational Technology, 37(2), 243–259. https://doi.org/10.1111/j.1467-8535.2005.00582.x
Article
Google Scholar
Huang, Y., & Liu, X. (2021). The analysis and research of STEAM education based on the TAM algorithm model to improve the learning effectiveness of higher vocational engineering students. Evolutionary Intelligence. https://doi.org/10.1007/s12065-021-00619-5
Article
Google Scholar
Huett, J. B. (2006). The Effects of ARCS-based Confidence Strategies on Learner Confidence and Performance in Distance Education. Citations.
Hwang, G.-J., Yang, L.-H., & Wang, S.-Y. (2013). A concept map-embedded educational computer game for improving students’ learning performance in natural science courses. Computers & Education, 69, 121–130. https://doi.org/10.1016/j.compedu.2013.07.008
Article
Google Scholar
Kanchanatanee, K., Suwanno, N., & Jarernvongrayab, A. (2014). Effects of Attitude toward Using, Perceived Usefulness, Perceived Ease of Use and Perceived Compatibility on Intention to Use E-Marketing. Journal of Management Research, 6, 3. https://doi.org/10.5296/jmr.v6i3.5573
Article
Google Scholar
Karakis, H., Karamete, A., & Okcu, A. (2016). The Effects of a Computer-Assisted Teaching Material, Designed According to the ASSURE Instructional Design and the ARCS Model of Motivation, on Students’ Achievement Levels in a Mathematics Lesson and Their Resulting Attitudes. European Journal of Contemporary Education, 15(1), 105–113. https://doi.org/10.13187/ejced.2016.15.105
Article
Google Scholar
Keller, J. M. (1983). Motivational design of instruction. Instructional Design Theories and Models: An Overview of Their Current Status, 1(1983), 383–434.
Google Scholar
Keller, J. M. (2009). Motivational design for learning and performance: The ARCS model approach. New York: Springer.
Google Scholar
Koc, E. S., & Ontas, T. (2020). A comparative analysis of the 4th and 5th grade social studies curriculum according to revised bloom taxonomy. Cypriot Journal of Educational Sciences, 15(3), 540–553. https://doi.org/10.18844/cjes.v15i3.4931.
Article
Google Scholar
Koul, R. B., & Fisher, D. L. (2005). Cultural Background and Students’ Perceptions of Science Classroom Learning Environment and Teacher Interpersonal Behaviour in Jammu. India. Learning Environments Research, 8(2), 195–211. https://doi.org/10.1007/s10984-005-7252-9
Article
Google Scholar
Kozlovskiy, Y., Bilyk, V., Zakharyash, O., Voloshyn, M., & Babkina, М. (2021). The information and communication technologies in the learning process of students in the context of cognitive development. Laplage em Revista, 7(3C), 471–476.
Article
Google Scholar
Krathwohl, D. R., Bloom, B. S., & Masia, B. B. (1973). Taxonomy of Educational Objectives, the Classification of Educational Goals. Handbook II: Affective Domain. New York: David McKay Co., Inc.
Land, M. H. (2013). 2013/01/01/). Full STEAM Ahead: The Benefits of Integrating the Arts Into STEM. Procedia Computer Science, 20, 547–552. https://doi.org/10.1016/j.procs.2013.09.317
Article
Google Scholar
Li, C.-L., Chen, Y.-H., & Li, H.-Y. (2018). Technical College Students’ ARCS Learning Motivation on Hospitality English Vocabulary. International Jouranl of Human Resource Studies, 8(1), 189–207. https://doi.org/10.5296/ijhrs.v8i1.12370
Article
Google Scholar
Li, K., & Moore, D. R. (2018). Motivating Students in Massive Open Online Courses (MOOCs) Using the Attention, Relevance, Confidence, Satisfaction (ARCS) Model. Journal of Formative Design in Learning, 2(2), 102–113. https://doi.org/10.1007/s41686-018-0021-9
Article
Google Scholar
Lin, K.-Y., Wu, Y.-T., Hsu, Y.-T., & Williams, P. J. (2021). Effects of infusing the engineering design process into STEM project-based learning to develop preservice technology teachers’ engineering design thinking. International Journal of STEM Education, 8(1), 1. https://doi.org/10.1186/s40594-020-00258-9
Article
Google Scholar
Lin, P.-Y., Chai, C.-S., Jong, M.S.-Y., Dai, Y., Guo, Y., & Qin, J. (2021). Modeling the structural relationship among primary students’ motivation to learn artificial intelligence. Computers and Education: Artificial Intelligence. https://doi.org/10.1016/j.caeai.2020.100006
Article
Google Scholar
Liu, C.-H. (2020). Local and international perspectives of the influence of creative experiences of Chinese traditional culture on revisit intentions. Current Issues in Tourism, 23(1), 17–35. https://doi.org/10.1080/13683500.2018.1564740
Article
Google Scholar
Liu, Q., Yu, S., Chen, W., Wang, Q., & Xu, S. (2021). The effects of an augmented reality based magnetic experimental tool on students’ knowledge improvement and cognitive load. Journal of Computer Assisted Learning, 37(3), 645–656. https://doi.org/10.1111/jcal.12513
Article
Google Scholar
Lohmöller, J.-B. (1989). Latent Variable Path Modeling with Partial Least Squares. Physica.
Book
Google Scholar
Loughlin-Presnal, J., & Bierman, K. L. (2017). How do parent expectations promote child academic achievement in early elementary school? A test of three mediators. Developmental Psychology, 53(9), 1694–1708. https://doi.org/10.1037/dev0000369
Article
Google Scholar
Lu, Y., Yeung, W.-J. J., & Treiman, D. J. (2020). Parental migration and children’spsychological and cognitive development in China: differences and mediating mechanisms. Chinese Sociological Review, 52(4), 337–363. https://doi.org/10.1080/21620555.2020.1776600.
Article
Google Scholar
Margot, K. C., & Kettler, T. (2019). Teachers’ perception of STEM integration and education: a systematic literature review. International Journal of STEM Education, 6(1), 2. https://doi.org/10.1186/s40594-018-0151-2.
Article
Google Scholar
Marín-Marín, J.-A., Moreno-Guerrero, A.-J., Dúo-Terrón, P., & López-Belmonte, J. (2021). STEAM in education: a bibliometric analysis of performance and co-words in Web of Science. International Journal of STEM Education, 8(1), 41. https://doi.org/10.1186/s40594-021-00296-x
Article
Google Scholar
Maskeliūnas, R., Kulikajevas, A., Blažauskas, T., Damaševičius, R., & Swacha, J. (2020). An Interactive Serious Mobile Game for Supporting the Learning of Programming in JavaScript in the Context of Eco-Friendly City Management. Computers, 9(4), 102. https://www.mdpi.com/2073-431X/9/4/102
Matthews, L. (2017). Applying multigroup analysis in PLS-SEM: A
step-by-step process. In (pp. 219-243).
Mu, R., & De Jong, M. (2018). The psychology of local officials: explaining strategic behavior in the Chinese Target Responsibility System. Journal of Chinese Governance, 3(2), 243–260. https://doi.org/10.1080/23812346.2018.1455413
Article
Google Scholar
Munawaroh, M. (2020). The Influence of Problem-Based Learning Model as Learning Method, and Learning Motivation on Entrepreneurial Attitude. International Journal of Instruction, 13(2), 431–444. https://doi.org/10.29333/iji.2020.13230a
Article
Google Scholar
Musavi, M., Friess, W. A., James, C., & Isherwood, J. C. (2018). Changing the face of STEM with stormwater research. International Journal of STEM Education, 5(1), 2. https://doi.org/10.1186/s40594-018-0099-2.
Article
Google Scholar
Mutambara, D., & Bayaga, A. (2021). Determinants of mobile learning acceptance for STEM education in rural areas. Computers & Education, 160, 104010. https://doi.org/10.1016/j.compedu.2020.104010
Article
Google Scholar
Ngah, A. H., Rashid, R. A., Ariffin, N. A., Ibrahim, F., Osman, N. A. A., Kamalrulzaman, N. I., Mohamad, M. F. H., & Harun, N. O. (2021). Fostering Students’ Attitude Towards Online Learning: the Mediation Effect of Satisfaction and Perceived Performance. https://easychair.org/publications/preprint/VMxp
Ocak, G., & Tepe, M., & Olur, B. (2020). Investigation of the objectives of the information technologh and sofeware course to the revised Bloom taxonomy. European Journal of Education Studies, 6(12), 56–68. https://doi.org/10.46827/ejes.v0i0.2857.
Article
Google Scholar
Olmedo Moreno, E. M., de Luna, E. B., Olmos Gómez, M. D. C., & López, J. E. (2014). Structural Equations Model (SEM) of a questionnaire on the evaluation of intercultural secondary education classrooms. Suma Psicológica, 21(2), 107–115. https://doi.org/10.1016/S0121-4381(14)70013-X.
Article
Google Scholar
Paas, F. (1992). 12/01). Training Strategies for Attaining Transfer of Problem-Solving Skill in Statistics: A Cognitive-Load Approach. Journal of Educational Psychology, 84, 429–434. https://doi.org/10.1037/0022-0663.84.4.429
Article
Google Scholar
Paas, F., Tuovinen, J. E., Tabbers, H., & Van Gerven, P. W. (2003). Cognitive load measurement as a means to advance cognitive load theory. Educational Psychologist, 38(1), 63–71. https://doi.org/10.1207/S15326985EP3801_8
Article
Google Scholar
Pabalan, N., Singian, E., Tabangay, L., Jarjanazi, H., Boivin, M. J., & Ezeamama, A. E. (2018). Soil-transmitted helminth infection, loss of education and cognitive impairment in school-aged children: A systematic review and meta-analysis. PLoS Negl Trop Dis, 12(1), e0005523. https://doi.org/10.1371/journal.pntd.0005523.
Article
Google Scholar
Pangarso, A., Astuti, E. S., Raharjo, K., & Afrianty, T. W. (2020). Data of innovation ambidexterity as a mediator in the absorptive capacity effect on sustainable competitive advantage. Data in Brief, 29, 105200. https://doi.org/10.1016/j.dib.2020.105200
Article
Google Scholar
Peter, J. P. (1981). Construct validity: A review of basic issues and marketing practices. Journal of Marketing Research, 18(2), 133–145. https://doi.org/10.2307/3150948
Article
Google Scholar
Quaid, E., Pack, A., Barrett, A., & Zhou, L. (2020, 12/13). Students' intention to use high-immersion virtual reality systems for learning paragraph structure: a PLS-SEM exploratory study. 291–297. https://doi.org/10.14705/rpnet.2020.48.1203
Radhamani, R., Kumar, D., Nizar, N., Achuthan, K., Nair, B., & Diwakar, S. (2021). What virtual laboratory usage tells us about laboratory skill education pre- and post-COVID-19: Focus on usage, behavior, intention and adoption. Education and Information Technologies. https://doi.org/10.1007/s10639-021-10583-3.
Article
Google Scholar
Ramma, Y., Bholoa, A., Watts, M., & Nadal, P. S. (2018). Teaching and learning physics using technology: Making a case for the affective domain. Education Inquiry, 9(2), 210–236. https://doi.org/10.1080/20004508.2017.1343606.
Article
Google Scholar
Sam Liu, C.-H. (2017). Remodelling progress in tourism and hospitality students’ creativity through social capital and transformational leadership. Journal of Hospitality, Leisure, Sport & Tourism Education, 21, 69–82. https://doi.org/10.1016/j.jhlste.2017.08.003.
Article
Google Scholar
Shernoff, D. J., Sinha, S., Bressler, D. M., & Ginsburg, L. (2017). Assessing teacher education and professional development needs for the implementation of integrated approaches to STEM education. International Journal of STEM Education, 4(1), 1–16. https://doi.org/10.1186/s40594-017-0068-1.
Article
Google Scholar
Shiau, S., Huang, C.-Y., Yang, C.-L., & Juang, J.-N. (2018). A Derivation of Factors Influencing the Innovation Diffusion of the OpenStreetMap in STEM Education. Sustainability, 10, 10. https://doi.org/10.3390/su10103447
Article
Google Scholar
Simpson, E. J. (1972). The Classification of Educational Objectives in the Psychomotor Domain. Gryphon House.
Google Scholar
Su, C.-H. (2019). The Effect of Users’ Behavioral Intention on Gamification Augmented Reality in Stem (Gar-Stem) Education. Journal of Baltic Science Education, 18(3), 450–465. https://doi.org/10.33225/jbse/19.18.450
Article
Google Scholar
Su, C. H., & Cheng, C. H. (2015). A mobile gamification learning system for improving the learning motivation and achievements. Journal of Computer Assisted Learning, 31(3), 268–286. https://doi.org/10.1111/jcal.12088
Article
Google Scholar
Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285.
Article
Google Scholar
Sweller, J., Van Merrienboer, J. J., & Paas, F. G. (1998a). Cognitive architecture and instructional design. Educational Psychology Review, 10(3), 251–296.
Article
Google Scholar
Sweller, J., van Merrienboer, J. J. G., & Paas, F. G. W. C. (1998b). Cognitive Architecture and Instructional Design. Educational Psychology Review, 10(3), 251–296. https://doi.org/10.1023/A:1022193728205
Article
Google Scholar
Tan, D. Y., & Cheah, C. W. (2021). Developing a gamified AI-enabled online learning application to improve students’ perception of university physics. Computers and Education: Artificial Intelligence, 2, 100032. https://doi.org/10.1016/j.caeai.2021.100032
Article
Google Scholar
Teo, T. (2009). Modelling technology acceptance in education: A study of pre-service teachers. Computers & Education, 52(2), 302–312. https://doi.org/10.1016/j.compedu.2008.08.006
Article
Google Scholar
Trujillo, L. T. (2019). Mental effort and information-processing costs are inversely related to global brain free energy during visual categorization. Frontiers in Neuroscience, 13, 1292. https://doi.org/10.3389/fnins.2019.01292
Article
Google Scholar
Voorhees, C. M., Brady, M. K., Calantone, R., & Ramirez, E. (2016). Discriminant validity testing in marketing: an analysis, causes for concern, and proposed remedies. Journal of the Academy of Marketing Science, 44(1), 119–134. https://doi.org/10.1007/s11747-015-0455-4
Article
Google Scholar
Wahyudi, S., Joyoatmojo, S., & Sawiji, H. (2017). Learning Model of Attention, Relevance, Confidence, Satisfaction (ARCS) supported by video tutorial to improve the students’ learning motivation in vocational high school. Advances in Social Science Education and Humanities Research (ASSEHR), 158, 603–611. https://doi.org/10.2991/ictte-17.2017.72
Article
Google Scholar
Wahono, B., Lin, P.-L., & Chang, C.-Y. (2020). Evidence of STEM enactment effectiveness in Asian student learning outcomes. International Journal of STEM Education, 7(1), 36. https://doi.org/10.1186/s40594-020-00236-1.
Article
Google Scholar
Weng, F., Yang, R.-J., Ho, H.-J., & Su, H.-M. (2018). A TAM-Based Study of the Attitude towards Use Intention of Multimedia among School Teachers. Applied System Innovation, 1, 3. https://doi.org/10.3390/asi1030036
Article
Google Scholar
Wu, B., & Chen, X. (2017). Continuance intention to use MOOCs: Integrating the technology acceptance model (TAM) and task technology fit (TTF) model. Computers in Human Behavior, 67, 221–232. https://doi.org/10.1016/j.chb.2016.10.028
Article
Google Scholar
Yafie, E., Nirmala, B., Kurniawaty, L., Bakri, T. S. M., Hani, A. B., & Setyaningsih, D. (2020). Supporting Cognitive Development through Multimedia Learning and Scientific Approach: An Experimental Study in Preschool. Universal Journal of Educational Research, 8(11C), 113–123. https://doi.org/10.13189/ujer.2020.082313.
Article
Google Scholar
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 39. https://doi.org/10.1186/s41239-019-0171-0.
Article
Google Scholar
Zhang, S.-N., Li, Y.-Q., Liu, C.-H., & Ruan, W.-Q. (2019). Critical factors in the identification of word-of-mouth enhanced with travel apps: the moderating roles of Confucian culture and the switching cost view. Asia Pacific Journal of Tourism Research, 24(5), 422–442. https://doi.org/10.1080/10941665.2019.1572630
Article
Google Scholar
Zhu, S., Yang, H. H., MacLeod, J., Yu, L., & Wu, D. (2019). Investigating Teenage Students’ Information Literacy in China: A Social Cognitive Theory Perspective. The Asia-Pacific Education Researcher, 28(3), 251–263. https://doi.org/10.1007/s40299-019-00433-9
Article
Google Scholar
Zorluoglu, S. L., Bagriyanik, K. E., & Sahintürk, A. (2019). Analyze of the Science and Technology Course TEOG Questions Based on the Revised Bloom Taxonomy and Their Relation between the Learning Outcomes of the Curriculum. International Journal of Progressive Education, 15(2), 104–117.
Article
Google Scholar