Eurasia Journal of Mathematics, Science and Technology Education

• Adiguzel, T. (2008). Dependability and acceptability of handheld computers in school-based data collection. Doctoral dissertation, College Station, TX: Texas A&M University. Retreived from http://hdl.handle.net/1969.1/ETD -TAMU -2958
• Adiguzel, T., Capraro, R. M., & Willson, V. L. (2011). An examination of teacher acceptance of handheld computers. International Journal of Special Education, 26(3), 12-27.
• Akça, Y. & Özer, G. (2012). The Use of Technology Acceptance Model in Enterprise Resource Planning Implementation. Business and Economics Research Journal, 3(2), 79-96.
• Alemán, J. L. F. (2011). Automated assessment in a programming tools course. IEEE Transactions on Education, 54(4), 576-581.
• Annett, J. (1969). Feedback and human behavior. Hammondsworth, England: Penguin.
• Barker, T. (2010). An Automated Feedback System Based on Adaptive Testing: Extending the Model. International Journal of Emerging Technologies in Learning, 5(2), 11-15.
• Baron, R. A. (1988). Negative effects of destructive criticism impact on conflict, self-efficacy, and task performance. Journal of Applied Psychology,73, 199–207.
• Barringer, C. & Gholson, B. (1979). Effects of type and combination of feedback upon conceptual learning by children: Implications for research in academic learning. Review of Educational Research, 49(3), 459-478.
• Brosnan, M. J. (1998). The impact of computer anxiety and self‐efficacy upon performance. Journal of computer assisted learning, 14(3), 223-234.
• Can, Ş. (2010). Comparison of the attitudes of the pre-service teachers from SESMTE and SESSTE departments against computer use (The case of Muğla University, Turkey). Procedia-Social and Behavioral Sciences, 2(2), 4638- 4642.
• Carpenter, D., Dolan, D., Leahy, D., & Sherwood-Smith, M. (2000). ECDL/ICDL: a global computer literacy initiative. In Proceedings of Conference on Educational Uses of Information and Communication Technologies (ICEUT), Beijing: Publishing House of Electronics Industry (PHEI).
• Cheang, B., Kurnia, A., Lim, A., & Oon, W. C. (2003). On automated grading of programming assignments in an academic institution. Computers & Education, 41(2), 121- 131.
• Chen, P. M. (2004). An Automated Feedback System for Computer Organization Projects. IEEE Transactions on Education , 47(2), 232-240.
• Clariana, R. B., Wagner, D., & Murphy, L. C. R. (2000). Applying a Connectionist Description of Feedback Timing. EducationalTechnology Research and Development, 48(3), 5-21.
• Creswell, J. W. (2003). Qualitative, quantitative, and mixed methods approaches (2nd Ed.) Thousand Oaks, CA: Sage.
• Çalışkan, H. (1998). Bilgisayar destekli öğretimde geri bildirim. Kurgu Dergisi, 15, 346-360.
• 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.
• Dempsey, J. V., & Driscoll, M. P. (1989). The Effects of Four Methods of Immediate Corrective Feedback on Retention, Discrimination Error, and Feedback Study Time in Computer-Based Instruction. American Educational Research Association Annual Meeting, San Francisco, CA.
• Driscoll, M. P. (1993). Psychology of earning for instruction. Needham Height, MA: Ally&Bacon.
• English, J. (2004). Automated assessment of GUI programs using JEWL. ACM SIGCSE Bulletin, 36(3), 137-141.
• Foubister, S. P., Michaelson, G. J., & Tomes, N. (1997). Automatic Assessment of Elementary Standard ML Programs Using Ceilidh. Journal of Computer Assisted Learning , 13, 99-108.
• Gist, M. E., Schwoerer, C., & Rosen, B. (1989). Effects of alternative training methods on self-efficacy and performance in computer software training. Journal of applied psychology, 74(6), 884.
• Goldstein, I. L., Emanuel, J. T., & Howell, W. C. (1968). Effect of percentage and specificity of feedback on choice behavior in a probabilistic informationprocessing task. Journal of Applied Psychology, 52, 163–168.
• Goodman, J. S., & Wood, R. E. (2004). Feedback Specificity, Learning Opportunities, and Learning. Journal of Applied Psychology, 89(5), 809–821.
• Helmick, M. T. (2007). Interface-based programming assignments and automatic grading of java programs. ACM SIGCSE Bulletin, 39(3), 63-67.
• Henninger, M., & Viswanathan, V. (2004). Social presence in online tutoring: What we know and what we should know. In Proceedings of the first joint meeting of the EARLI SIGs instructional design and learning and instruction with computers (CD-ROM). Tuebingen: Knowledge Media Research Center.
• Higgins, C. A., Gray, G., Symeonidis, P., & Tsintsifas, A. (2005). Automated assessment and experiences of teaching programming. Journal on Educational Resources in Computing (JERIC), 5(3), 5.
• Hu, P. J., Chau, P. Y., Liu Sheng, O. R., & Tam, K. Y. (1999). Examining the technology acceptance model using physician acceptance of telemedicine technology. Journal of Management Information Systems, 16(2), 91-112.
• Jackson, D., & Usher, M. (1997). Grading student programs using ASSYST. ACM SIGCSE Bulletin, 29(1), 335-339.
• Johnson, R. B., & Onwuegbuzie, A. J. (2004). Mixed methods research: A research paradigm whose time has come. Educational Researcher, 33(7), 14-26.
• Kopelman, R. E. (1986). Objective feedback. In E. A. Locke (Ed.), Generalizing from laboratory to field settings (pp. 119– 145). Lexington, MA: D. C. Heath.
• Kulik, J. A., & Kulik, C. C. (1988). Timing of feedback and verbal learning. Review of Educational Research, 58(1), 79- 97.
• Laakso, M. J., Salakoski, T., Grandell, L., Qiu, X., Korhonen, A., & Malmi, L. (2005a). Multi-perspective study of novice learners adopting the visual algorithm simulation exercise system TRAKLA2. Informatics in Education: An International Journal, 4(1), 49-68.
• Laakso, M. J., Salakoski, T., & Korhonen, A. (2005b). The Feasibility of Automatic Assessment and Feedback. IADIS International Conference on Cognition and Exploratory Learning in Digital Age (pp. 113-122). Porto: IADIS.
• Ma, W. W., Andersson, R., & Streith, K. O. (2005). Examining user acceptance of computer technology: An emprical study of student teachers. Journal of Computer Assisted Learning, 21, 387-395.
• Malmi, L., Korhonen, A., & Saikkonen, R. (2002). Experiences in automatic assessment on mass courses and issues for designing virtual courses. ACM SIGCSE Bulletin, 34(3), 55-59.
• Morris, D. S. (2003). Automatic Grading of Student's Programming Assignments: An Interactive Process and Suite of Programs. 33rd Annual Frontiers in Education. 3, S3F1-S3F6. Westminster, USA: FIE.
• Mory, E. H. (2003). Feedback research revisited. In Jonassen, J.H. (Ed.): Handbook of Research on Educational Communications and Technology, MacMillian Library Reference, New York, pp.745–783.
• Narciss, S., Körndle, H., Reimann, G., & Müller, C. (2004). Feedback-seeking and feedback efficiency in web-based learning – How do they relate to task and learner characteristics? In Gerjets, P., Kirschner, P. A., Elen, J. & Joiner, R. (Eds.). Proceedings of the first joint meeting of the EARLI SIGs Instructional Design and Learning and Instruction with Computers (pp. 377-388). Tuebingen: Knowledge Media Research Center.
• Payne, R. B., & Hauty, B. T. (1955). Effect of psychological feedback upon work decrement. Journal of Experimental Psychology, 50, 343–351.
• Russell, B. W. (1992). The effect of computer-generated instructional feedback and videotape on the speaking performance of college students in a basic speech course. Doctoral dissertation, Pittsburgh, PA: University of Pittsburgh.
• Saikkonen, R., Malmi, L., & Korhonen, A. (2001). Fully Automatic Assessment of Programming Exercises. 6th Annual Conference on Innovation and Technology in Computer Science Education (pp. 133-136). New York: ACM.
• Schmidt, R. A. (1991). Frequent augmented feedback can degrade learning: Evidence and interpretations. In J. Requin & G. E. Steimach (Eds.), Tutorials in motor neuroscience (pp. 59–75). London: Kluwer Academic.
• Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(1), 144-176.
• Teo, T., Ursavaş, Ö. F., & Bahçekapılı, E. (2012). An assessment of pre-service teachers’ technology acceptance in Turkey: A structural equation modeling approach. The Asia-Pacific Education Researcher, 21(1), 191- 202.
• Tosti, D., & Jackson, S. (1999). Feedback. In H. Stolovich & E. Keeps (ed) Handbook of Performance Technology, (2nd. Ed.), (pp. 395-410). San Francisco: Jossey-Bass/Pfeiffer.
• Usluel Koçak, Y. & Mazman, S. G. (2009). Sosyal Ağların Benimsenmesi Ölçeği. Eğitim Bilimleri ve Uygulama Dergisi, 8(15), 137-157.
• Varank, I. (2007). Effectiveness of quantitative skills, qualitative skills, and gender in determining computer skills and attitudes: A causal analysis. The Clearing House, 81(2), 71-80.
• Vasilyeva, E., Puuronen, S., Pechenizkiy, M., & Räsänen, P. (2007). Feedback adaptation in web-based learning systems. International Journal of Continuing Engineering Education and Life-Long Learning, 17(4/5), 337-357.
• Wager, W., & Wager, S. (1985). Presenting questions, processing responses, and providing feedback in CAI. Journal of Instructional Development, 8(4), 2–8.
• Wang, T., Su, X., Ma, P., Wang, Y., & Wang, K. (2011). Ability-training-oriented automated assessment in introductory programming course. Computers & Education, 56(1), 220-226.
• Wentling, T. L. (1973). Mastery versus nonmastery instructions with varying test item feedback treatments. Journal of Educational Psychology, 65, 50–58.
• Yi, M. Y., & Im, K. S. (2004). Predicting computer task performance: personal goal and self-efficacy. Journal of Organizational and End User Computing (JOEUC), 16(2), 20-37.

APA

Varank, İ., Erkoç, M. F., Büyükimdat, M. K., Aktaş, M., Yeni, S., Adıgüzel, T., Cömert, Z., & Esgin, E. (2014). Effectiveness of an Online Automated Evaluation and Feedback System in an Introductory Computer Literacy Course. Eurasia Journal of Mathematics, Science and Technology Education, 10(5), 395-404. https://doi.org/10.12973/eurasia.2014.1062a

Vancouver

Varank İ, Erkoç MF, Büyükimdat MK, Aktaş M, Yeni S, Adıgüzel T, et al. Effectiveness of an Online Automated Evaluation and Feedback System in an Introductory Computer Literacy Course. EURASIA J Math Sci Tech Ed. 2014;10(5):395-404. https://doi.org/10.12973/eurasia.2014.1062a

AMA

Varank İ, Erkoç MF, Büyükimdat MK, et al. Effectiveness of an Online Automated Evaluation and Feedback System in an Introductory Computer Literacy Course. EURASIA J Math Sci Tech Ed. 2014;10(5), 395-404. https://doi.org/10.12973/eurasia.2014.1062a

Chicago

Varank, İlhan, M. Fatih Erkoç, Meryem Köşkeroğlu Büyükimdat, Mehmet Aktaş, Sabiha Yeni, Tufan Adıgüzel, Zafer Cömert, and Esad Esgin. "Effectiveness of an Online Automated Evaluation and Feedback System in an Introductory Computer Literacy Course". Eurasia Journal of Mathematics, Science and Technology Education 2014 10 no. 5 (2014): 395-404. https://doi.org/10.12973/eurasia.2014.1062a

Harvard

Varank, İ., Erkoç, M. F., Büyükimdat, M. K., Aktaş, M., Yeni, S., Adıgüzel, T., . . . Esgin, E. (2014). Effectiveness of an Online Automated Evaluation and Feedback System in an Introductory Computer Literacy Course. Eurasia Journal of Mathematics, Science and Technology Education, 10(5), pp. 395-404. https://doi.org/10.12973/eurasia.2014.1062a

MLA

Varank, İlhan et al. "Effectiveness of an Online Automated Evaluation and Feedback System in an Introductory Computer Literacy Course". Eurasia Journal of Mathematics, Science and Technology Education, vol. 10, no. 5, 2014, pp. 395-404. https://doi.org/10.12973/eurasia.2014.1062a