Eurasia Journal of Mathematics, Science and Technology Education

• Abbasi, S., Moeini, M., Shahriari, M., Ebrahimi, M., Khoozani, E. K. (2018). Designing and manufacturing of educational multimedia software for preventing coronary artery disease and its effects on modifying the risk factors in patients with coronary artery disease. Electronic Journal of General Medicine, 15(3), em22. https://doi.org/10.29333/ejgm/85942.
• Agarwal, B., & Mittal, N. (2014). Text classification using machine learning methods-a survey. In Proceedings of the Second International Conference on Soft Computing for Problem Solving (SocProS 2012), December 28-30, 2012 (pp. 701-709). Springer, New Delhi. https://doi.org/10.1007/978-81-322-1602-5_75.
• Alickovic, E., & Subasi, A. (2016). Medical decision support system for diagnosis of heart arrhythmia using DWT and random forests classifier. Journal of medical systems, 40(4), 1. https://doi.org/10.1007/s10916-016-0467-8.
• Atenas, J., & Havemann, L. (2014). Questions of quality in repositories of open educational resources: a literature review. Research in Learning Technology, 22(1), 20889. https://doi.org/10.3402/rlt.v22.20889.
• Bartholomew, S. (2015). My journey with self-directed learning. Techniques: Connecting Education & Careers, 90(2), 46-50.
• Cai, S., Wang, X., & Chiang, F. K. (2014). A case study of Augmented Reality simulation system application in a chemistry course. Computers in Human Behavior, 37, 31–40. https://doi.org/10.1016/j.chb.2014.04.018.
• Chao, P. Y. (2016). Exploring students’ computational practice, design and performance of problem-solving through a visual programming environment. Computers & Education, 95, 202-215. https://doi.org/10.1016/j.compedu.2016.01.010.
• Chen, C. M., & Chen, F. Y. (2014). Enhancing digital reading performance with a collaborative reading annotation system. Computer and Education, 77, 67-81. https://doi.org/10.1016/j.compedu.2014.04.010.
• de Almeida Cruz, J. J., & de Azevedo Silva, K. K. (2017). Relational Algebra Teaching Support Tool. Journal of Information Systems Engineering & Management, 2(2), 8. https://doi.org/10.20897/jisem.201708.
• Jin, X., Zhao, M., Chow, T. W., & Pecht, M. (2014). Motor bearing fault diagnosis using trace ratio linear discriminant analysis. IEEE Transactions on Industrial Electronics, 61(5), 2441-2451. https://doi.org/10.1109/TIE.2013.2273471.
• Jude, L. T., Kajura, M. A., & Birevu, M. P. (2014). Adoption of the SAMR Model to Assess ICT Pedagogical Adoption: A Case of Makerere University. International Journal of e-Education, e-Business, e-Management and e-Learning, 4(2), 106-115. https://doi.org/10.7763/IJEEEE.2014.V4.312.
• Khalid, S., Khalil, T., & Nasreen, S. (2014). A survey of feature selection and feature extraction techniques in machine learning. In Science and Information Conference (SAI), 2014 (pp. 372-378). IEEE. https://doi.org/10.1109/SAI.2014.6918213.
• Kuo, C. L., & Chao, C. Y. (2014). Exploring the relationship among patterns, information technology, and performance for SME-based service innovation. International Journal of Electronic Business Management, 12(2), 101-110.
• Lee, L. C., & Hao, K. C. (2015). Designing and Evaluating Digital Game-Based Learning with the ARCS Motivation Model, Humor, and Animation. International Journal of Technology and Human Interaction, 11(2), 80-95. https://doi.org/10.4018/ijthi.2015040105.
• Maeng, U., & Lee, S. M. (2015). EFL teachers’ behavior of using motivational strategies: The case of teaching in the Korean context. Teaching and Teacher Education, 46, 25–36. https://doi.org/10.1016/j.tate.2014.10.010.
• Manek, A. S., Shenoy, P. D., Mohan, M. C., & Venugopal, K. R. (2017). Aspect term extraction for sentiment analysis in large movie reviews using Gini Index feature selection method and SVM classifier. World wide web, 20(2), 135-154. https://doi.org/10.1007/s11280-015-0381-x.
• MichelaMortara, M., Catalanoa, C. E., Bellotti, F., Fiucci, G., Houry-Panchetti, M., & Panagiotis, P. (2014). Learning cultural heritage by serious games. Journal of Cultural Heritage, 15(3), 318–325. https://doi.org/10.1016/j.culher.2013.04.004.
• Molaee, Z., & Dortaj, F. (2015). Improving L2 Learning: An ARCS Instructional-motivational Approach. Procedia - Social and Behavioral Sciences, 171, 1214-1222. https://doi.org/10.1016/j.sbspro.2015.01.234.
• Ng, E. M. (2016). Fostering pre-service teachers’ self-regulated learning through self-and peer assessment of wiki projects. Computers & Education, 98, 180-191. https://doi.org/10.1016/j.compedu.2016.03.015.
• Nikou, S. A., & Economides, A. A. (2017). Mobile-based assessment: Investigating the factors that influence behavioral intention to use. Computers & Education, 109, 56-73. https://doi.org/10.1016/j.compedu.2017.02.005.
• Reid-Griffin, A., & Slaten, K. M. (2016). Wikis: Developing pre-service teachers’ leadership skills and knowledge of content standards. European Journal of STEM Education, 1(1), 3-7. https://doi.org/10.20897/lectito.201601.
• Rocha, T., Martins, J., Branco, F., & Gonçalves, R. (2017). Evaluating Youtube Platform Usability by People with Intellectual Disabilities (A User Experience Case Study Performed in a Six-Month Period). Journal of Information Systems Engineering & Management, 2(1), 5. https://doi.org/10.20897/jisem.201705.
• Romrell, D., Kidder, L. C., & Wood, E. (2014). The SAMR Model as a Framework for Evaluating m-Learning. Journal of Asynchronous Learning Networks, 18(2).
• Sáez-López, J. M., Román-González, M., & Vázquez-Cano, E. (2016). Visual programming languages integrated across the curriculum in elementary school: A two year case study using “Scratch” in five schools. Computers & Education, 97, 129-141. https://doi.org/10.1016/j.compedu.2016.03.003.
• Sanjay, G. (2016). A Comparative Study on Face Recognition using Subspace Analysis. In International Conference on Computer Science and Technology Allies in Research-March (p. 82).
• Shahabadi, M. M., & Uplane, M. (2014). Learning Styles and Academic Performance of Synchronous E-Learning Students. Asian Journal of Research in Social Sciences and Humanities, 4(5), 148-161.
• Subasi, A., Alickovic, E., & Kevric, J. (2017). Diagnosis of Chronic Kidney Disease by Using Random Forest. In CMBEBIH 2017 (pp. 589-594). Springer, Singapore. https://doi.org/10.1007/978-981-10-4166-2_89.
• Uysal, A. K., & Gunal, S. (2014). The impact of preprocessing on text classification. Information Processing & Management, 50(1), 104-112. https://doi.org/10.1016/j.ipm.2013.08.006.
• Valerie, C. B. (2015). Self-Directed Learning and Technology. Education Digest, 80(6), 42-44.
• Vanderhoven, E., Raes, A., Montrieux, H., Rotsaert, T., & Schellens, T. (2015). What if pupils can assess their peers anonymously? A quasi-experimental study. Computers & Education, 81, 123-132. https://doi.org/10.1016/j.compedu.2014.10.001.
• Woo, J. C. (2014). Digital Game-Based Learning Supports Student Motivation, Cognitive Success, and Performance Outcomes. Educational Technology & Society, 17(3), 291–307.
• Wu, C. H., & Kuo, C. L. (2014). Investigating the cross effects of smart devices, collaborative learning, and instructional designs on high school students’ learning outcome. In the Proceedings of the 2014 International Conference on e-Commerce, e-Administration, e-Society, e-Education, and e-Technology fall session (e-CASE & e-Tech 2014 fall session).

APA

Zhao, Y., & Ding, T. (2018). Effects of Digital Game-Based Experiential Learning on Students’ Ethical Instruction Effectiveness. Eurasia Journal of Mathematics, Science and Technology Education, 14(7), 3347-3354. https://doi.org/10.29333/ejmste/91243

Vancouver

Zhao Y, Ding T. Effects of Digital Game-Based Experiential Learning on Students’ Ethical Instruction Effectiveness. EURASIA J Math Sci Tech Ed. 2018;14(7):3347-54. https://doi.org/10.29333/ejmste/91243

AMA

Zhao Y, Ding T. Effects of Digital Game-Based Experiential Learning on Students’ Ethical Instruction Effectiveness. EURASIA J Math Sci Tech Ed. 2018;14(7), 3347-3354. https://doi.org/10.29333/ejmste/91243

Chicago

Zhao, Yue, and Tingting Ding. "Effects of Digital Game-Based Experiential Learning on Students’ Ethical Instruction Effectiveness". Eurasia Journal of Mathematics, Science and Technology Education 2018 14 no. 7 (2018): 3347-3354. https://doi.org/10.29333/ejmste/91243

Harvard

Zhao, Y., and Ding, T. (2018). Effects of Digital Game-Based Experiential Learning on Students’ Ethical Instruction Effectiveness. Eurasia Journal of Mathematics, Science and Technology Education, 14(7), pp. 3347-3354. https://doi.org/10.29333/ejmste/91243

MLA

Zhao, Yue et al. "Effects of Digital Game-Based Experiential Learning on Students’ Ethical Instruction Effectiveness". Eurasia Journal of Mathematics, Science and Technology Education, vol. 14, no. 7, 2018, pp. 3347-3354. https://doi.org/10.29333/ejmste/91243