The Relationship of Grade Expectation and Academic Achievement of College Students

Öz

Students’ motivation is an important factor in academic performance. The purpose of this study is to examine the relationship and interaction effects among college students' grade expectations, academic performance and perceptions of course difficulty. The sample of the study consists of 2,946 students enrolled at an university in Ankara. 11,294 responses of the students to the Teaching Quality Assesment Questionnaire and grades of students form the study’s data. The dependency relationship between students' expected grade and received grades was examined with the Chi-square test of independence. In addition, multilevel frequency analysis and log linear analysis were applied to determine the interactions between the levels of expected grade, received grade and perceived difficulty level of the course variables. The study found that students who received high grades had expectations that closely aligned with their actual grades, while students who received low grades had expectations that were less aligned. In other words, as students' academic achievement increases, their expectations of their grades and the grades they receive align more closely. Another finding is a negative relationship between an increase in the perceived difficulty of the course and the likelihood of expecting and receiving high grades. The findings are discussed in terms of Expectancy Theory, Goal Setting Theory and the Dunning-Kruger effect.

Anahtar Kelimeler

• higher education
• academic achievement
• motivation
• Dunning Kruger Effect

Üniversite Öğrencilerinin Not Beklentileri ve Akademik Başarıları Arasındaki İlişki

Öz

Öğrenci motivasyonu akademik performansta önemli bir faktördür. Bu çalışmanın amacı, üniversite öğrencilerinin not beklentileri, akademik performansları ve ders zorluğu algıları arasındaki ilişkiyi ve değişkenler arasındaki etkileşimi incelemektir. Çalışmanın örneklemini, Ankara’daki bir üniversitede kayıtlı 2946 öğrenci oluşturmaktadır. Araştırma verileri, öğrencilerin Öğretim Kalitesi Değerlendirme Anketi'ne verdiği 11294 yanıt ve öğrencilerin notlarıdır. Öğrencilerin not beklentileri ile aldıkları notlar arasındaki bağımlılık ilişkisi Ki-kare bağımsızlık testi ile incelenmiştir. Ayrıca beklenen not, alınan not ve ders zorluğu algısı değişkenlerinin düzeyleri arasındaki etkileşimleri belirlemek için çok düzeyli frekans analizi ve log lineer analiz uygulanmıştır. Çalışma sonucunda, yüksek not alan öğrencilerin beklentilerinin notlarıyla yüksek oranda uyumlu olduğu, düşük not alan öğrencilerin beklentilerinin ise notlarıyla daha az uyumlu olduğu görülmüştür. Başka bir deyişle, öğrencilerin akademik başarıları arttıkça, notlarına ilişkin beklentileri ile aldıkları notlar uyumlu olmaktadır. Bir diğer bulgu, dersin algılanan zorluğundaki artış ile yüksek not bekleme ve alma olasılığı arasındaki negatif ilişkidir. Bulgular Beklenti Kuramı, Hedef Belirleme Kuramı ve Dunning-Kruger etkisi açısından tartışılmıştır.

Anahtar Kelimeler

• yükseköğretim
• akademik başarı
• motivasyon
• Dunning Kruger Etkisi

Kaynakça

1. Aktaş Altunay, S., Yılmaz, A.E., Bahçecitapar, M. & Bakacak Karabenli, L. (2021). SPSS ve R uygulamalı kategorik veri çözümlemesi, [Categorical data analysis with SPSS and R]. Ankara: Seçkin Yayıncılık.
2. Andersen, E. (1994). The statistical analysis of categorical data. Berlin: SpringerVerlag.
3. Bandura, A. (1997). Self-efficacy: The exercise of control, New York: Freeman.
4. Burson, A. K., Larrıck, P. R., & Klayman, J. (2006). Skilled or unskilled, but still unaware of it: How perceptions of difficulty drive miscalibration in relative comparisons. In Journal of Personality and Social Psychology, 90(1), p. 67. https://doi.org/10.1037/0022-3514.90.1.60
5. Chen, X. E., & Latham, G. P. (2014). The effect of priming learning vs performance goals on a complex task. Organizational Behavior and Human Decision Processes, 125, 88–97. http://dx.doi.org/10.1016/j.obhdp.2014.06.004
6. Chiang, C. F., & Jang, S. S. (2008). An expectancy theory model for hotel employee motivation. International Journal of Hospitality Management, 27(2), 313-322. https://doi.org/10.1016/j.ijhm.2007.07.017
7. Christensen, (1997). Log-linear models and logistic regression (2nd ed.). New York: Springer.
8. Christie, H., Munro, M., & Fisher, T. (2004). Leaving university early: Exploring the differences between continuing and noncontinuing students. Studies in Higher Education. https://doi.org/10.1080/0307507042000261580

9. Couchman, J. J., Miller, N., Zmuda, S. J., Feather, K., and Schwartzmeyer, T. (2016). The instinct fallacy: the metacognition of answering and revising during college exams. Metacogn. Learn. 11, 171–185. https://doi.org/10.1007/s11409-015- 9140-8
10. Coutinho, M. V. C., Papanastasiou, E., Agni, S., Vasko, J. M., and Couchman, J. J. (2020). Metacognitive monitoring in test-taking situations: a cross-cultural comparison of college students. Int. J. Instruction 13, 407–424 https://zuscholars.zu.ac.ae/works/2378
11. Coutinho, M. V. C., Thomas, J., Fredricks-Lowman, I., Alkaabi, S., & Couchman, J. J. (2024). Unskilled and unaware: second-order judgments increase with miscalibration for low performers. Frontiers in Psychology, 15, 1252520. https://doi.org/10.3389/fpsyg.2024.1252520
12. Coutinho, M. V., Thomas, J., Lowman, I. F., & Bondaruk, M. V. (2020). The DunningKruger effect in Emirati college students: Evidence for generalizability across cultures. International Journal of Psychology and Psychological Therapy, 20(1), 29-36. https://dialnet.unirioja.es/servlet/articulo?codigo=7288616
13. De Bruin, A. B. H., Kok, E., Lobbestael, J., and De Grip, A. (2017). The impact of an online tool for monitoring and regulating learning at university: overconfidence, learning strategy, and personality. Metacogn. Learn, 12, 21–43. https://doi.org/10.1007/s11409- 016-9159-5
14. DiYanni, R., and A. Borst. (2020). Motivating Student Learning. In The Craft of College Teaching: A Practical Guide, edited by R. DiYanni and A. Borst, 8–21. Princeton: Princeton University Press.
15. Ehrlinger J & Dunning AD (2003). How chronic self-views influence (and mislead) estimates of performance. Journal of Personality and Social Psychology, 84, 5- 17. https://doi.org/10.1037/00223514.84.1
16. Dunning, D., Heath, C., and Suls, J. M. (2004). Flawed self-assessment: implications for health, education, and the workplace. Psychol. Sci. Public Interest 5, 69–106. https://doi.org/10.1111/j.1529-1006.2004.00018.
17. Dunning, D., Johnson, K., Ehrlinger, J., and Kruger, J. (2003). Why people fail to recognize their own incompetence. Curr. Dir. Psychol. Sci, 12, 83–87. https://doi.org/10.1111/1467-8721.01235
18. Ehrlinger, J., Johnson, K., Banner, M., Dunning, D., & Kruger, J. (2008). Why the unskilled are unaware: Further explorations of (absent) self-insight among the incompetent. Organizational Behavior and Human Decision Processes, 105(1), 98-121. https://doi.org/10.1016/j.obhdp.2007.05.002
19. Estes, B., & Polnick, B. (2012). Examining motivation theory in higher education: An expectancy theory analysis of tenured faculty productivity. International Journal of MBA, 1, 13-19. nationalforum.com
20. Feather, N.T. (1992). Values, Valences, Expectations, and Actions. Journal of Social Issue, 48(2): 109-124 https://doi.org/10.1111/j.1540-4560.1992.tb00887.x
21. Field, A. (2009). Discovering statistics using SPSS statistics (3rd ed.). SAGE Publications.
22. Foster, N. L., Was, C. A., Dunlosky, J., & Isaacson, R. M. (2017). Even after thirteen class exams, students are still overconfident: The role of memory for past exam performance in student predictions. Metacognition and Learning, 12, 1–19. https://doi.org/10.1007/s11409-016-9158-6 .
23. Fraenkel JR, Wallen NE ve Hyunn, H.H. (2012). How to design and evaluate research in education (8th ed.). Mc Graw Hill Higher Education. New York: NY.
24. Friedman, B. A., & Mandel, R. G. (2009). The Prediction of College Student Academic Performance and Retention: Application of Expectancy and Goal Setting Theories. Journal of College Student Retention: Research, Theory & Practice, 11(2), 227-246. https://doi.org/10.2190/CS.11.2.d
25. Fritzsche, E. S., Handel, M., & Kroner, S. (2018). What do second-order judgments tell us about low-performing students' metacognitive awareness? Metacognition and Learning, 13, 159–177. https://doi.org/10.1007/s11409-018-9182-9.
26. Geiger, M. A., & Cooper, E. A. (1995). Predicting academic performance: The impact of expectancy and needs theory. The Journal of Experimental Education, 63(3), 251-262. https://doi.org/10.1080/00220973.1995.9943812
27. Green, J.A. (1988). Loglinear analysis of cross-classified ordinal data: applications in developmental research. Society for Research in Child Development, 59(1), 1-25. https://doi.org/10.2307/1130385
28. Greenacre, M.J. (2010), Correspondence analysis. WIREs Comp Stat, 2: 613- 619.https://doi.org/10.1002/wics.114
29. Griffin, L., & Harrell, A. (1991). An empirical examination of managers' motivation to implement just-in-time procedures. Journal of Management Accounting Research, 3, 98-112.
30. Hancock, D. R. (1991). Effects of conceptual levels and direct and non-direct instruction patterns on achievement and motivation in course content (Order No. 9136325). Available from ProQuest Dissertations & Theses Global. (303965331). Retrieved from https://www.proquest.com/dissertationstheses/effects-conceptual-levels-direct-non-instruction/docview/303965331/se-2
31. Hancock, D. R. (1995). What teachers may do to influence student motivation: An application of expectancy theory. The Journal of General Education, 44(3), 171- 179. https://www.jstor.org/stable/27797259
32. Handel, M., & Fritzsche, E. S. (2016). Unskilled but subjectively aware: Metacognitive monitoring ability and respective awareness in low-performing students. Memory & Cognition, 44, 229–241. https://doi.org/10.3758/s13421-015-0552-0 .
33. Heine SJ, Takata T, & Lehman DR (2000). Beyond self-presentation: Evidence for Japanese self-criticism. Personality and Social Psychology Bulletin, 26, 71-78. https://doi.org/10.1177/0146167200261007
34. Hofstede G (1980). Culture’s Consequences: International Differences in WorkRelated Values. Beverly Hills, CA: Sage.
35. Howell, D.C. (2010) Statistical methods for psychology (7th ed.). Wadsworth Cengage Learning, Belmont. https://journals.sagepub.com/doi/pdf/10.1177/1536867X0 600600302
36. Hulleman, C. S., Schrager, S. M., Bodmann, S. M., and Harackiewicz, J. M. (2010). A metaanalytic review of achievement goal measures: different labels for the same constructs or different constructs with similar labels? Psychol. Bull. 136, 422– 449. https://doi.org/10.1037/a0018947
37. Karatjas, A. G. (2013). Comparing college students’ self-assessment of knowledge in organic chemistry to their actual performance. Journal of Chemical Education, 90(8), 1096-1099. https://doi.org/10.1021/ed400037p
38. Kirkman, B. L., & Shapiro, D. (1997). The impact of cultural values on employee resistance to teams: A comparative analysis of self-managing work team effectiveness in Belgium, Finland, the Philippines, and the United States. Academy of Management Review, 22, 730–757. https://doi.org/10.5465/amr.1997.9708210724
39. Kitayama S, Markus HR, Matsumoto H, & Norasakkunkit V (1997). Individual and collective processes in the construction of the self: Self-enhancement in the United States and self-criticism in Japan. Journal of Personality and Social Psychology, 72, 1245-1267. https://doi.org/10.1037/0022-3514.72.6.124
40. Kruger, J., Dunnıng, D. (1999). Unskilled and unaware of ıt: How difficulties in recognizing one’s own incompetence lead to inflated self-assessments. In Journal of Personality and Social Psychology, Vol. 77 (6), p. 1132. https://doi.org/10.1037/0022-3514.77.6.1121 Latham, G. P., & Locke, E. A. Increasing productivity with decreasing time limits: A field replication of Parkinson's law. Journal of Applied Psychology, 1975, 60, 524-526.
41. Latham, G. P., Brcic, J., & Steinhauer, A. (2017). Toward an integration of goal setting theory and the automaticity model. Applied Psychology, 66, 25–48. http://dx.doi.org/10.1111/apps.12087
42. Lee, S. (2007). Vroom's expectancy theory and the public library customer motivation model. Library Review. DOI: 10.1108/00242530710831239
43. Lindsey, B. A., & Nagel, M. L. (2015). Do students know what they know? Exploring the accuracy of students’ self-assessments. Physical Review Special TopicsPhysics Education Research, 11(2), 020103. https://doi.org/10.1103/PhysRevSTPER.11.020103
44. Locke, E. A. (1968). Toward a theory of task motivation and incentives. Organizational Behavior and Human Performance, 3(2), 157-189 https://doi.org/10.1016/0030-5073(68)90004-4
45. Locke, E. A., & Latham, G. P. (1990). A theory of goal setting & task performance. Englewood Cliffs, NJ: Prentice-Hall, Inc.
46. Locke, E. A., & Latham, G. P. (2019). The development of goal setting theory: A half century retrospective. Motivation Science, 5(2), 93. https://doi.org/10.1037/mot0000127
47. Locke, E. A., Latham, G. P., & Erez, M. (1988). The determinants of goal commitment. Academy of Management Review, 13, 23–39. https://doi.org/10.5465/amr.1988.4306771
48. Lu, B., Deng, Y., Yao, X., and Li, Z. (2022). Learning goal orientation and academic performance: a dynamic model. J. Career Assess. 30, 329–344. https://doi.org/10.3390/su14106304
49. Mahmood, K. (2016). Do people overestimate their information literacy skills? A systematic review of empirical evidence on the Dunning-Kruger effect. Communications in Information Literacy, 10(2), 3. https://doi.org/10.15760/comminfolit.2016.10.2.24
50. Malloch, D. C., & Michael, W. B. (1981). Predicting student grade point average at a community college from Scholastic Aptitude Tests and from measures representing three constructs in Vroom's expectancy theory model of motivation. Educational and Psychological Measurement, 41(4), 1127-1135. https://doi.org/10.1177/001316448104100422
51. Maznevski, M. L., DiStefano, J. J., Gomez, C. B., Noorderhaven, N. G., & Wu, P. (1997). The cultural orientations framework and international management research. Paper presented at the Academy of International Business annual meeting, Guadalajara, Mexico.
52. Mento, A. J., Locke, E. A., & Klein, H. (1992). Relationship of goal level to valence and instrumentality. Journal of Applied Psychology, 77, 395–405. http://dx.doi.org/10.1037/0021-9010.77.4.395
53. Metsämuuronen, J. (2020). Somers’ D as an alternative for the item–test and item-rest correlation coefficients in the educational measurement settings. International Journal of Educational Methodology, 6(1), 207‒221. https://doi.org/10.12973/ijem.6.1.207
54. Miller, T. M., & Geraci, L. (2011). Training metacognition in the classroom: The influence of incentives and feedback on exam predictions. Metacognition and Learning, 6, 303–314. https://doi.org/10.1007/s11409-011-9083-7 .
55. Miner, J. B. (2015). Expectancy theories: Victor Vroom, and Lyman Porter and Edward Lawler. In Organizational behavior 1 (pp. 110-129). Routledge. 9781315702018
56. Moody, S., Bowden, R., Brock, J., & Bunch, P. (2022). College Student Aspiration as a Motivation for Engagement: The Road to Academic Success? Journal of College Student Retention: Research, Theory & Practice, 24(3), 856-878. https://doi.org/10.1177/1521025120957594
57. Moore, D., & Healy, P. (2008). The Trouble with Overconfidence. In Psychological Review, Vol. 115, No. 2, p. 502. https://doi.org/10.1037/0033-295X.115.2.50
58. Newson, R. (2002). Parameters behind “nonparametric” statistics: Kendall’s tau, Somers’ D and median differences. The Stata Journal, 2 (1),45–64. https://journals.sagepub.com/doi/pdf/10.1177/1536867X0200200103
59. Newson, R. (2006). Confidence intervals for rank statistics: Somers’ D and extensions. The Stata Journal. 6 (3), 309–334
60. Pazicni, S., & Bauer, C. F. (2014). Characterizing illusions of competence in introductory chemistry students. Chemistry Education Research and Practice, 15(1), 24-34. https://doi.org/10.1039/C3RP00106G
61. Pekrun, R. (1993). Facets of students' academic motivation: A longitudinal expectancy value approach. In M. L. Maehr, & P. R. Pintrich (Vol. Eds.), Advances in motivation and achievement, 8 (139–189). Greenwich, CT: JAI Press
62. Pennycook G, Ross R, Koehler D, & Fugelsang J (2017). Dunning-Kruger effects in reasoning: Theoretical implications of the failure to recognize incompetence. Psychonomic Bulletin & Review, 24, 1774-1784. https://doi.org/10.3758/s13423- 017-1242-7
63. Pinxten, M., Marsh, H. W., De Fraine, B., Noortgate, W. V. D., & Dame, J. V. (2014). Enjoying mathematics or feeling competent in mathematics? Reciprocal effects on mathematics achievement and perceived math effort expenditure. British Journal of Educational Psychology, 84, 152–174. https://doi.org/10.1111/bjep.12028.
64. Putwain, D. W., Nicholson, L. J., Pekrun, R., Becker, S., & Symes, W. (2019). Expectancy of success, attainment value, engagement, and achievement: A moderated mediation analysis. Learning and instruction, 60, 117-125.
65. Rebello, N. S. (2012, February). How accurately can students estimate their performance on an exam and how does this relate to their actual performance on the exam? In AIP Conference Proceedings (Vol. 1413, No. 1, pp. 315-318). American Institute of Physics. https://doi.org/10.1063/1.3680058
66. Richardson, M., Abraham, C., & Bond, R. (2012). Psychological correlates of university students’ academic performance: A systematic review and metaanalysis. Psychological Bulletin, 138(2), 353–387. https://doi.org/10.1037/a0026838
67. Robbins, S. B., Le, H., Davis, D., Lauver, K., Langley, R., & Carlstrom, A. (2004). Do psychosocial and study skill factors predict college outcomes?. A Meta-Analysis.
68. Psychological Bulletin, 130(2), 261–288. https://doi.org/10.1037/0033- 2909.130.2.261
69. Robbins, S. P., & Judge, T. (2012). Essentials of organizational behavior. ISBN: 13:978-0-13-254530-3
70. Ryan, R. M., & Deci, E. L. (2020). Intrinsic and extrinsic motivation from a selfdetermination theory. In E. Q. Rosenzweig, A. Wigfield, & J. S. Eccles (Eds.), 61. Expectancy-value theory and its relevance for student motivation and learning perspective: Definitions, theory, practices, and future directions (p. 101860). Contemporary Educational Psychology. https://doi.org/10.1016/j.cedpsych.2020.101860 .
71. Sanchez, C., and Dunning, D. (2018). Overconfidence among beginners: is a little learning a dangerous thing? J. Pers. Soc. Psychol. 114, 10–28. https://doi.org/10.1037/pspa000 0102
72. Scholl, R. W. (2002). Motivational processes – Expectancy theory. Retrieved from http://www.uri.edu/research/lrc/scholl/Notes/MotivationExpectancy.html at September, 20, 2021
73. Sheldon JO, Ames RD, & Dunning D (2014). Emotionally unskilled, unaware, and uninterested in learning more: Reactions to feedback about deficits in emotional intelligence. Journal of Applied Psychology, 99, 125-137. https://doi.org/10.1037/a0034138
74. Snead, K. C. (1991). An application of expectancy theory to examine managers' motivation to utilize a decision support system. Journal of Management Accounting Research, 3, 213-222
75. Steinmayr, R., & Spinath, B. (2009). The importance of motivation as a predictor of school achievement. Learning and Individual Differences, 19, 80–90. https://doi.org/10.1016/j.lindif.2008.05.004
76. Suciu, L. E., Mortan, M., & Lazăr, L. (2013). Vroom's expectancy theory. An empirical study: Civil servant's performance appraisal influencing expectancy. Transylvanian Review of Administrative Sciences, 9(39), 180-200.
77. Sue-Chan, C., & Ong, M. (2002). Goal assignment and performance: Assessing the mediating roles of goal commitment and self-efficacy and the moderating role of power distance. Organizational Behavior and Human Decision Processes, 89(2), 1140-1161. https://doi.org/10.1016/S0749-5978(02)00017-1
78. Urdan, T., & Kaplan, A. (2020). The origins, evolution, and future directions of achievement goal theory. Contemporary Educational Psychology, 61, Article 101862. https://doi.org/10.1016/j.cedpsych.2020.101862
79. Van den Broek, A., Warps, J., de Korte, K., Cuppen, J., Termorshuizen, T., & Lodewick, J. (2019). Monitor Beleidsmaatregelen 2019- 2020: Studiekeuze, studiegedrag & leengedrag in relatie tot beleidsmaatregelen in het hoger onderwijs. ResearchNed.
80. Vollmer, F. (1986). The relationship between expectancy and academic achievement—How can it be explained? British Journal of Educational Psychology, 56(1), 64-74. https://doi.org/10.1111/j.2044-8279.1986.tb02646.x
81. Vroom, V.H. (1964). Work and motivation. Oxford, England: Wiley.
82. Wigfield, A., & Eccles, J. S. (2020). 35 years of research on students’ subjective task values and motivation: A look back and a look forward. In , vol. 7. Advances in motivation science (pp. 161–198). https://doi.org/10.1016/bs.adms.2019.05.002
83. Wirthwein, L., Sparfeldt, J. R., Pinquart, M., Wegerer, J., and Steinmayr, R. (2013). Achievement goals and academic achievement: a closer look at moderating factors. Educ. Res. Rev. 10, 66–89. https://doi.org/10.1016/j.edurev.2013.07.001
84. Wu, Z. (2019). Academic Motivation, Engagement, and Achievement among College Students. College Student Journal 53 (1): 99–112. link.gale.com/apps/doc/A584328141/AONE?u=anon~72e030bf&sid=googleSc holar&xid=bae39ec5.
85. Yukl, G. A., & Latham, G. P. Interrelationships among employee participation, individual differences, goal difficulty, goal acceptance, goal instrumentality, and performance. Personnel Psychology, 31, 305- 323.