Research Article
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Year 2025, Volume: 14 Issue: 1, 115 - 129, 29.01.2025

Abstract

References

  • Bennedsen, J., and Caspersen, M. E. (2007) Failure rates in introductory programming. SIGCSE Bulletin, 39(2):32{36, 2007.
  • Bol, L., Hacker, D. J., O'Shea, P., & Allen, D. (2005). The influence of overt practice, achievement level, and explanatory style on calibration accuracy and performance. The Journal of Experimental Education, 73(4), 269-290.
  • Connolly, T. M., & Begg, C. E. (2007). Teaching database analysis and design in a web-based vonstructivist learning environment. In Web Information Systems and Technologies: International Conferences, WEBIST 2005 and WEBIST 2006 Revised Selected Papers (pp. 343-354). Springer Berlin Heidelberg.
  • Douglas, D. E., & Van Der Vyver, G. (2004). Effectiveness of e-learning course materials for learning database management systems: An experimental investigation. Journal of Computer Information Systems, 44(4), 41-48.
  • Erat, S., Demirkol, K., & Sallabas, M. E. (2022). Overconfidence and its link with feedback. Active Learning in Higher Education, 23(3), 173-187. https://doi.org/10.1177/1469787420981731
  • Erdemir, T., & Somyürek, S. (2023). Overconfidence and Measurement Methods: Literature Review. Trakya Journal of Education. 13(2).1402-1420.
  • Etemad, M., & Küpçü, A. (2018). Verifiable database outsourcing supporting join. Journal of Network and Computer Applications, 115, 1-19. https://doi.org/10.1016/j.jnca.2018.04.006
  • Gezgin, D. M. (2019). The effect of mobile learning approach on university students' academic success for database management systems course. International Journal of Distance Education Technologies (IJDET), 17(1), 15-30. https://doi.org/10.4018/IJDET.2019010102
  • Hacker, D. J., Bol, L., Horgan, D. D., & Rakow, E. A. (2000). Test prediction and performance in a classroom context. Journal of Educational Psychology, 92(1), 160. https://doi.org/10.1037/0022-0663.92.1.160
  • Hacker, D. J., Bol, L., & Keener, M. C. (2008). Metacognition in education: A focus on calibration. In J. Dunlosky & R. A. Bjork (Eds.), Handbook of metamemory and memory (pp. 429–455). Psychology Press.
  • Hamzah, M. L., Rukun, K., Rizal, F., & Purwati, A. A. (2019). A review of increasing teaching and learning database subjects in computer science. Revista Espacios, 40(26).
  • Keller, J. (2002). Blatant stereotype threat and women's math performance: Self-handicapping as a strategic means to cope with obtrusive negative performance expectations. Sex Roles, 47(3-4), 193-198.
  • Kruger, J., & Dunning, D. (1999). Unskilled and unaware of it: how difficulties in recognizing one's own incompetence lead to inflated self-assessments. Journal of personality and social psychology, 77(6), 1121.
  • Lai Mooi, T. (2006). Self‐efficacy and student performance in an accounting course. Journal of Financial Reporting and Accounting, 4(1), 129-146. https://doi.org/10.1108/19852510680001586
  • Larrick, R. P., Burson, K. A., & Soll, J. B. (2007). Social comparison and confidence: When thinking you’re better than average predicts overconfidence (and when it does not). Organizational Behavior and Human Decision Processes, 102(1), 76-94. https://doi.org/10.1016/j.obhdp.2006.10.002
  • Miller, T. M., & Geraci, L. (2011). Unskilled but aware: Reinterpreting overconfidence in low-performing students. Journal of Experimental Psychology: Learning, Memory, and Cognition, 37(2), 502-506. https://doi.org/10.1037/a0021802
  • Moore, D. A., & Healy, P. J. (2008). The trouble with overconfidence. Psychological review, 115(2), 502-517. https://doi.org/10.1037/0033-295X.115.2.502
  • Moore, D. A., Tenney, E. R., & Haran, U. (2015). Overprecision in judgment. In G. Keren & G. Wu (Eds.), The Wiley Blackwell handbook of judgment and decision making, 2, 182-209.
  • Moore, D. A., & Schatz, D. (2017). The three faces of overconfidence. Social and Personality Psychology Compass, 11(8), e12331. https://doi.org/10.1111/spc3.12331
  • Morien, R. I. (2006). A Critical Evaluation Database Textbooks, Curriculum and Educational Outcomes. Director, 7.
  • Murray, M., & Guimaraes, M. (2009). Animated courseware support for teaching database design. Issues in Informing Science and Information Technology, 6, 201-211. https://doi.org/10.28945/1053
  • Nagataki, H., Nakano, Y., Nobe, M., Tohyama, T., & Kanemune, S. (2013, November). A visual learning tool for database operation. In Proceedings of the 8th Workshop in Primary and Secondary Computing Education (pp. 39-40). https://doi.org/10.1145/2532748.2532771
  • Nowell, C., & Alston, R. M. (2007). I thought I got an A! Overconfidence across the economics curriculum. The Journal of Economic Education, 38(2), 131-142. https://doi.org/10.3200/JECE.38.2.131-142
  • Olsson, H. (2014). Measuring overconfidence: Methodological problems and statistical artifacts. Journal of Business Research, 67(8), 1766-1770. https://doi.org/10.1016/j.jbusres.2014.03.002
  • Özçelik, D. A. (1992). Ölçme ve değerlendirme. [Assessment and evaluation ] Ankara: ÖSYM.
  • Paese, P. W., & Sniezek, J. A. (1991). Influences on the appropriateness of confidence in judgment: Practice, effort, information, and decision-making. Organizational Behavior and Human Decision Processes, 48(1), 100-130. https://doi.org/10.1016/0749-5978(91)90008-H
  • Poščić, P., Subotić, D., & Ivašić-Kos, M. (2012, May). Developing the course Database systems to respond to market requirements. In 2012 Proceedings of the 35th International Convention MIPRO (pp. 1141-1145). IEEE.
  • Schanbacher, P. (2013). Is the log score in line with forecasters’ preferences?. International Journal of Applied Decision Sciences, 6(4), 406-430. https://doi.org/10.1504/IJADS.2013.056882
  • Steele, C. M., Spencer, S. J., & Aronson, J. (2002). Contending with group image: The psychology of stereotype and social identity threat. In Advances in experimental social psychology (Vol. 34, pp. 379-440). Academic Press. https://doi.org/10.1016/S0065-2601(02)80009-0
  • Somyürek, S., & Brusilovsky, P. (2015, October). Impact of open social student modeling on self-assessment of performance. In E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 1181-1188). Association for the Advancement of Computing in Education (AACE).
  • Somyürek, S., Brusilovsky, P., & Guerra, J. (2020). Supporting knowledge monitoring ability: open learner modeling vs. open social learner modeling. Research and Practice in Technology Enhanced Learning, 15(1), 1-24.
  • Somyürek, S., & Çelik, İ. (2018). Dunning-Kruger sendromu ve öznel değerlendirmeler. Eğitim Teknolojisi Kuram ve Uygulama, 8(1), 141-157.
  • Sözbilir, M. (2010). Madde analizi ve test geliştirme. [Content analysis and test development].
  • Tobias, S., & Everson, H. T. (2002). Knowing what you know and what you don’t: Further research on metacognitive knowledge monitoring. Research Report No. 2002-3. College Entrance Examination Board.
  • Watson, C., & Li, F. W. (2014, June). Failure rates in introductory programming revisited. In Proceedings of the 2014 conference on Innovation & technology in computer science education (pp. 39-44). https://doi.org/10.1145/2591708.2591749

Analyzing Academic Achievement and Overconfidence in Database Management Systems Course: A Case Study of Computer and Instructional Technology Education Students

Year 2025, Volume: 14 Issue: 1, 115 - 129, 29.01.2025

Abstract

Decision-making tends to be more accurate and of higher quality when there's a sensible harmony between self-confidence and actual capabilities. Overconfidence makes it difficult to set realistic goals in academic settings and increases the likelihood of facing failure. In this study, the academic achievements and overconfidence of students enrolled in the Database Management Systems course were examined. The research also aimed to determine whether there is a difference between midterm and final exams in terms of these variables. The participants were comprised of students enrolled in the Computer and Instructional Technologies Education department of a state university throughout the 2021-2022 academic year. The results indicated that approximately two-thirds of the students did not achieve satisfactory academic scores. Students struggled to accurately assess their exam performances, and a significant number of them overestimated their positions in both the midterm and final exams. Furthermore, there was no significant change between the midterm and final exams for any of the three factors.

Ethical Statement

Araştırmanın etik izni Ankara Gazi Üniversitesi Eğitim Bilimleri Enstitüsü Etik Komitesi tarafından onaylanmıştır. Etik kurul belge numarası 23.05.2023- 664509

Supporting Institution

Destekleyen Kurum Yok

References

  • Bennedsen, J., and Caspersen, M. E. (2007) Failure rates in introductory programming. SIGCSE Bulletin, 39(2):32{36, 2007.
  • Bol, L., Hacker, D. J., O'Shea, P., & Allen, D. (2005). The influence of overt practice, achievement level, and explanatory style on calibration accuracy and performance. The Journal of Experimental Education, 73(4), 269-290.
  • Connolly, T. M., & Begg, C. E. (2007). Teaching database analysis and design in a web-based vonstructivist learning environment. In Web Information Systems and Technologies: International Conferences, WEBIST 2005 and WEBIST 2006 Revised Selected Papers (pp. 343-354). Springer Berlin Heidelberg.
  • Douglas, D. E., & Van Der Vyver, G. (2004). Effectiveness of e-learning course materials for learning database management systems: An experimental investigation. Journal of Computer Information Systems, 44(4), 41-48.
  • Erat, S., Demirkol, K., & Sallabas, M. E. (2022). Overconfidence and its link with feedback. Active Learning in Higher Education, 23(3), 173-187. https://doi.org/10.1177/1469787420981731
  • Erdemir, T., & Somyürek, S. (2023). Overconfidence and Measurement Methods: Literature Review. Trakya Journal of Education. 13(2).1402-1420.
  • Etemad, M., & Küpçü, A. (2018). Verifiable database outsourcing supporting join. Journal of Network and Computer Applications, 115, 1-19. https://doi.org/10.1016/j.jnca.2018.04.006
  • Gezgin, D. M. (2019). The effect of mobile learning approach on university students' academic success for database management systems course. International Journal of Distance Education Technologies (IJDET), 17(1), 15-30. https://doi.org/10.4018/IJDET.2019010102
  • Hacker, D. J., Bol, L., Horgan, D. D., & Rakow, E. A. (2000). Test prediction and performance in a classroom context. Journal of Educational Psychology, 92(1), 160. https://doi.org/10.1037/0022-0663.92.1.160
  • Hacker, D. J., Bol, L., & Keener, M. C. (2008). Metacognition in education: A focus on calibration. In J. Dunlosky & R. A. Bjork (Eds.), Handbook of metamemory and memory (pp. 429–455). Psychology Press.
  • Hamzah, M. L., Rukun, K., Rizal, F., & Purwati, A. A. (2019). A review of increasing teaching and learning database subjects in computer science. Revista Espacios, 40(26).
  • Keller, J. (2002). Blatant stereotype threat and women's math performance: Self-handicapping as a strategic means to cope with obtrusive negative performance expectations. Sex Roles, 47(3-4), 193-198.
  • Kruger, J., & Dunning, D. (1999). Unskilled and unaware of it: how difficulties in recognizing one's own incompetence lead to inflated self-assessments. Journal of personality and social psychology, 77(6), 1121.
  • Lai Mooi, T. (2006). Self‐efficacy and student performance in an accounting course. Journal of Financial Reporting and Accounting, 4(1), 129-146. https://doi.org/10.1108/19852510680001586
  • Larrick, R. P., Burson, K. A., & Soll, J. B. (2007). Social comparison and confidence: When thinking you’re better than average predicts overconfidence (and when it does not). Organizational Behavior and Human Decision Processes, 102(1), 76-94. https://doi.org/10.1016/j.obhdp.2006.10.002
  • Miller, T. M., & Geraci, L. (2011). Unskilled but aware: Reinterpreting overconfidence in low-performing students. Journal of Experimental Psychology: Learning, Memory, and Cognition, 37(2), 502-506. https://doi.org/10.1037/a0021802
  • Moore, D. A., & Healy, P. J. (2008). The trouble with overconfidence. Psychological review, 115(2), 502-517. https://doi.org/10.1037/0033-295X.115.2.502
  • Moore, D. A., Tenney, E. R., & Haran, U. (2015). Overprecision in judgment. In G. Keren & G. Wu (Eds.), The Wiley Blackwell handbook of judgment and decision making, 2, 182-209.
  • Moore, D. A., & Schatz, D. (2017). The three faces of overconfidence. Social and Personality Psychology Compass, 11(8), e12331. https://doi.org/10.1111/spc3.12331
  • Morien, R. I. (2006). A Critical Evaluation Database Textbooks, Curriculum and Educational Outcomes. Director, 7.
  • Murray, M., & Guimaraes, M. (2009). Animated courseware support for teaching database design. Issues in Informing Science and Information Technology, 6, 201-211. https://doi.org/10.28945/1053
  • Nagataki, H., Nakano, Y., Nobe, M., Tohyama, T., & Kanemune, S. (2013, November). A visual learning tool for database operation. In Proceedings of the 8th Workshop in Primary and Secondary Computing Education (pp. 39-40). https://doi.org/10.1145/2532748.2532771
  • Nowell, C., & Alston, R. M. (2007). I thought I got an A! Overconfidence across the economics curriculum. The Journal of Economic Education, 38(2), 131-142. https://doi.org/10.3200/JECE.38.2.131-142
  • Olsson, H. (2014). Measuring overconfidence: Methodological problems and statistical artifacts. Journal of Business Research, 67(8), 1766-1770. https://doi.org/10.1016/j.jbusres.2014.03.002
  • Özçelik, D. A. (1992). Ölçme ve değerlendirme. [Assessment and evaluation ] Ankara: ÖSYM.
  • Paese, P. W., & Sniezek, J. A. (1991). Influences on the appropriateness of confidence in judgment: Practice, effort, information, and decision-making. Organizational Behavior and Human Decision Processes, 48(1), 100-130. https://doi.org/10.1016/0749-5978(91)90008-H
  • Poščić, P., Subotić, D., & Ivašić-Kos, M. (2012, May). Developing the course Database systems to respond to market requirements. In 2012 Proceedings of the 35th International Convention MIPRO (pp. 1141-1145). IEEE.
  • Schanbacher, P. (2013). Is the log score in line with forecasters’ preferences?. International Journal of Applied Decision Sciences, 6(4), 406-430. https://doi.org/10.1504/IJADS.2013.056882
  • Steele, C. M., Spencer, S. J., & Aronson, J. (2002). Contending with group image: The psychology of stereotype and social identity threat. In Advances in experimental social psychology (Vol. 34, pp. 379-440). Academic Press. https://doi.org/10.1016/S0065-2601(02)80009-0
  • Somyürek, S., & Brusilovsky, P. (2015, October). Impact of open social student modeling on self-assessment of performance. In E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 1181-1188). Association for the Advancement of Computing in Education (AACE).
  • Somyürek, S., Brusilovsky, P., & Guerra, J. (2020). Supporting knowledge monitoring ability: open learner modeling vs. open social learner modeling. Research and Practice in Technology Enhanced Learning, 15(1), 1-24.
  • Somyürek, S., & Çelik, İ. (2018). Dunning-Kruger sendromu ve öznel değerlendirmeler. Eğitim Teknolojisi Kuram ve Uygulama, 8(1), 141-157.
  • Sözbilir, M. (2010). Madde analizi ve test geliştirme. [Content analysis and test development].
  • Tobias, S., & Everson, H. T. (2002). Knowing what you know and what you don’t: Further research on metacognitive knowledge monitoring. Research Report No. 2002-3. College Entrance Examination Board.
  • Watson, C., & Li, F. W. (2014, June). Failure rates in introductory programming revisited. In Proceedings of the 2014 conference on Innovation & technology in computer science education (pp. 39-44). https://doi.org/10.1145/2591708.2591749
There are 35 citations in total.

Details

Primary Language English
Subjects Other Fields of Education (Other)
Journal Section Articles
Authors

Seren Güzelyurt Karabay 0009-0001-7569-9720

Sibel Somyürek 0000-0001-7803-1438

Publication Date January 29, 2025
Submission Date December 16, 2023
Acceptance Date February 1, 2024
Published in Issue Year 2025 Volume: 14 Issue: 1

Cite

APA Güzelyurt Karabay, S., & Somyürek, S. (2025). Analyzing Academic Achievement and Overconfidence in Database Management Systems Course: A Case Study of Computer and Instructional Technology Education Students. Bartın University Journal of Faculty of Education, 14(1), 115-129.

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Bartın University Journal of Faculty of Education