Predicting students' performance in project-based learning: a substantiation of an interdisciplinary study
Keywords:
effectiveness, project-based learning, forecasting, higher education, assessment of performance, neural network technologies
Abstract
Introduction. Constant changes, a continuous flow of information, and uncertainty require a person, being a subject of professional activity, to be effective and achieve maximum performance while preserving psychological resources. Therefore, personal effectiveness and its prediction are of urgent importance both for an individual and for an organization. Aims: to study the phenomenon of effective performance, in particular project performance, and its psychological factors, as well as to find ways to predict personal effectiveness in project performance. The theoretical basis includes the following principles: a systematic approach to the key psychological parameters of project performance; interaction and development as a system-dynamic approach to self-organization in uncertain, critical situations; the principle of performance in personality studies and the study of individual and joint activities. A literature review was performed as a systematic analysis of original theoretical and empirical studies available on Science Direct, eLibrary, Google Scholar, and Scopus. Results. A review of theoretical and empirical studies provides grounds for defining effectiveness as a measure of qualitative and quantitative assessment of performance, which is determined both by its content and by a complex of various psychological characteristics. Understanding the requirements for project performance and creating optimal conditions for it with respect to the psychological characteristics of subjects provide the possibility for an adequate assessment of effectiveness and its forecast within a differentiated approach to the training of specialists. Conclusion. Artificial intelligence is the most promising technology for predicting performance effectiveness, which confirms the need for interdisciplinary research and further study.
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References
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55. Rastrollo-Guerrero J.L., Gómez-Pulido J.A., Durán-Domínguez A. Analyzing and Predicting Students Performance by Means of Machine Learning: A Review. Applied sciences. 2020;10(3). DOI: 10.3390/app10031042.
56. Namoun A., Alshanqiti A. Predicting Student Performance Using Data Mining and Learning Analytics Techniques: A Systematic Literature Review. Applied Sciences. 2021;11(1). DOI: 10.3390/app11010237.
2. Chen C.H., Yang Y.C. Revisiting the effects of project-based learning on students academic achievement: A meta-analysis investigating moderators. Educational Research Review. 2019;26:71–81. DOI: 10.1016/j.edurev.2018.11.001.
3. Guo P., Saab N., Post L.S. et al. A review of project-based learning in higher education: Student outcomes and measures. International journal of educational research. 2020;102:e101586. DOI: 10.1016/j.ijer.2020.101586.
4. Borovikov D.A. Efficiency as a socio-psychological category: ontological approach. Vestnik Udmurtskogo universiteta. Seriya Filosofiya. Psikhologiya. Pedagogika = Bulletin of Udmurt University. Series Philosophy. Psychology. Pedagogy. 2011;2:69–76. (in Russ.).
5. Slepko Yu.N. Content of the concept of “effectiveness of professional activity”. Yaroslavskii pedagogicheskii vestnik = Yaroslavl Pedagogical Bulletin. 2010;2(4):193–197. (in Russ.).
6. Ivanova E.M. Psychology and efficiency of the subject of labor. Psikhologiya v ekonomike i upravlenii = Psychology in Economics and Management. 2013;1:6–12. (in Russ.).
7. Tverdovskaya A.V., Gnezdilov G.V. Criteria and performance indicators of professional activity of an entrepreneur and the specifics of his training. Chelovecheskii capital = Human capital. 2022;5-2(161):200–209. (in Russ.).
8. Cogliser C.C., Gardner W.L., Gavin M.B. et al. Big five personality factors and leader emergence in virtual teams: Relationships with team trustworthiness, member performance contributions, and team performance. Group and Organization Management. 2012;37(6):752–784. DOI: 10.1177/1059601112464266.
9. Druzhilov S.A. Performance efficiency and individual resource for professional development. Mezhdunarodnyi zhurnal prikladnykh i fundamentalnykh issledovanii = International Journal of Applied and Basic Research. 2014;4:161–164. (in Russ.).
10. Druzhilov S.A. Professional styles of a person and the effectiveness of his activities. Uspekhi sovremennogo estestvoznaniya = Advances of modern natural science. 2012;9:64–67. (in Russ.).
11. Demushkina O.S. Personal characteristics of project team employees as a factor in the effectiveness of project activities in the field of information technology. Azimut nauchnykh issledovanii: pedagogika i psikhologiya = Azimuth of scientific research: pedagogy and psychology. 2018;7(1):269–272. (in Russ.).
12. Ermolaeva M.V., Kokueva Zh.M. Psychological approaches to motivational processes in a project team. Izvestiya Irkutskogo gosudarstvennogo universiteta. Seriya: Psikhologiya = News of Irkutsk State University. Series: Psychology. 2019;28:20–34. (in Russ.).
13. Uchadze L.G. The influence of motivation to achieve success on the effectiveness of a manager. Gumanizatsiya obrazovaniya = Humanization of Education. 2009;1; 110–114. (in Russ.).
14. Belous V.V. Towards the study of the influence of temperament types on the effectiveness of individual and joint activities. Voprosy psikhologii = Issues of psychology. 1985;3:113–120. (in Russ.).
15. Dmitrieva Y.A., Korobova S.Y., Kochkina D.V. Individual response to stressors and efficiency in project activities. Behavioral Sciences. 2019;10(1). DOI: 10.3390/bs10010010.
16. Sergienko E.A., Khlevnaya E.A., Kiseleva T.S. The role of emotional intelligence in the effectiveness of activity and psychological well-being of a person. Vestnik Kostromskogo gosudarstvennogo universiteta. Seriya: Pedagogika. Psikhologiya. Sotsiokinetika = Bulletin of Kostroma State University. Series: Pedagogy. Psychology. Sociokinetics. 2020;26(1):46–53. (in Russ.).
17. Lobczowski N.G., Lyons K., Greene J.A. et al. Socioemotional regulation strategies in a project-based learning environment Contemporary Educational Psychology. 2021;65:e101968. DOI: 10.1016/j.cedpsych.2021.101968.
18. Markina N.V., Vyboishchik I.V., Pervukhina E.S., Gumnitskii M.E., Mikhailyuk L.G. Psychological resources of project activities of teachers included in subject Olympiads. Psikhologiya. Psikhofiziologiya = Psychology. Psychophysiology. 2021;14(2):27–37. (in Russ.).
19. Ngereja B., Hussein B., Andersen B. Does Project-Based Learning (PBL) Promote Student Learning? A Performance Evaluation. Education Sciences. 2020;10. DOI: 10.3390/educsci10110330.
20. Jitpaiboon T., Smith S., Gu Q. Critical Success Factors Affecting Project Performance: An Analysis of Tools, Practices, and Managerial Support. Project Management Journal. 2019;50:271–287. DOI: 10.1177/8756972819833545.
21. Sidorenkov A.V., Shtroo V.A. The role of the number of informal subgroups in the effectiveness of an industrial small group. Organizatsionnaya psikhologiya = Organizational psychology. 2023;13(1):35–58. (in Russ.).
22. Aranzabal A., Epelde E., Artetxe M. Team formation on the basis of Belbins roles to enhance students performance in project based learning. Education for Chemical Engineers. 2022;38:22–37. DOI: 10.1016/j.ece.2021.09.001.
23. Mergendoller J.R., Thomas J.W. Managing project based learning: Principles from the field. Buck Institute for Education. 2001. URL: https://dr-hatfield.com/science_rules/articles/ Managing%20Project%20Based%20Learning.pdf
24. Garcia-Martin J., Perez-Martinez J.E. Method to Guide the Design of Project Based Learning Activities Based on Educational Theories. International Journal of Engineering Education. 2017;33(3):984–999.
25. Klementeva M.V. Project activity as a resource for personal and professional development of students. Pisma v Emissiya. Offlain = Letters to Emission. Offline. 2018;7:26–34. (in Russ.).
26. Baranova T.A. Integration of student project activities into the educational process of a modern university. Sovremennye naukoemkie tekhnologii = Modern high technology. 2017;9:88–92. (in Russ.).
27. Shkunova A.A., Pleshanov K.A. Organization of project activities of students at a university: results of scientific research and development prospects. Vestnik Mininskogo universiteta = Bulletin of Minin University. 2017;4(21). (in Russ.). DOI: 10.26795/2307-1281-2017-4-4
28. Odarich I.N. Project activities in the educational process of the university. Nauchen vektor na Balkanite = Vector learned in Balkanite. 2017;1:18–21. (in Russ.).
29. Kovalenko Yu.A., Nikitina L.L. Project activities of students in the educational process of the university. Vestnik Kazanskogo tekhnologicheskogo universiteta = Bulletin of Kazan Technological University. 2012;15(20):229–231. (in Russ.).
30. Popova M.S. Project activity as a means of developing creative activity of university students. Gaudeamus. 2017;16(3):101–103. (in Russ.).
31. Cifrian E., Andres A., Galan B. et al. Integration of different assessment approaches: application to a project-based learning engineering course. Education for Chemical Engineers. 2020;31:62–75. DOI: 10.1016/j.ece.2020.04.006.
32. Schulz B. The Importance of Soft Skills: Education beyond academic knowledge. Journal of Language and Communication. 2008;2:146–154.
33. Vetrov Yu.P. Features of organizing project activities in vocational education. Vestnik Maikopskogo gosudarstvennogo tekhnologicheskogo universiteta = Bulletin of Maikop State Technological University. 2019;2:41–48. (in Russ.).
34. Barabanshchikova V.V., Kaminskaya E.O. The phenomenon of procrastination in the activities of members of virtual project groups. Natsionalnyi psikhologicheskii zhurnal = National Psychological Journal. 2013;2(10):43–51. (in Russ.).
35. Fernandes S., Dinis-Carvalho J., Ferreira-Oliveira A. Improving the Performance of Student Teams in Project-Based Learning with Scrum. Education Sciences. 2021;11. DOI: 10.3390/educsci11080444.
36. DeFillippi R.J. Introduction: Project-based learning, reflective practices and learning. Management learning. 2001;32(1):5–10. DOI: 10.1177/1350507601321001.
37. Safonova K.I., Podolskii S.V. Project activities of students at the university: planning projects and assessing the effectiveness of their implementation. Obshchestvo: sotsiologiya, psikhologiya, pedagogika = Society: sociology, psychology, pedagogy. 2018;5:83–94. (in Russ.).
38. Noordin M.K., Nordin M.S. Project-based learning (PjBL) framework in developing non-technical skills for engineering students. Advanced Science Letters. 2018;24(6):4515–4518. DOI: 10.1166/asl.2018.11640.
39. Toktarova V.I., Semenova D.A., Zaripov R.N. Assessing the effectiveness of students project activities based on their digital footprint. Vestnik Mariiskogo gosudarstvennogo universiteta = Bulletin of Mari State University. 2021;15(44):420–429. (in Russ).
40. Başbay M., Ateş A. The reflections of student teachers on project based learning and investigating self-evaluation versus teacher evaluation. Procedia – Social and Behavioral Sciences. 2009;1:242–247. DOI: 10.1016/j.sbspro.2009.01.044.
41. Matyash N.V., Volodina Yu.A. Methodology for assessing students project competence. Psikhologicheskie issledovaniya = Psychological research. 2011;4(17). (in Russ.).
42. Vasileva E.I., Zerchaninova T.E., Ruchkin A.V. Assessing the performance of civil servants. Upravlencheskoe konsultirovanie = Management consulting. 2016;4(88):14–26. (in Russ.).
43. Sultanova E.V., Ankudinova A.M. Assessing the effectiveness of project activities as a tool for developing leadership qualities of a civil servant. Azimut nauchnykh issledovanii: ekonomika i upravlenie = Research Azimuth: Economics and Management. 2019;8(26):67–70. (in Russ.).
44. Podkopaeva O.A. Forecasting, planning and modeling: an interdisciplinary approach and convergence of knowledge: monograph. Samara: Ofort LLC. 2015:351.
45. Gilev D.V., Mazurov V.D. Mathematical psychology, neural networks and recognition. Psikhologiya. Istoriko-kriticheskie obzory i sovremennye issledovaniya = Psychology. Historical-critical reviews and modern studies. 2019;8(3):21–27. (in Russ.).
46. Giannakas F., Troussas C., Voyiatzis I. et al. A deep learning classification framework for early prediction of team-based academic performance. Applied Soft Computing. 2021;106:e107355. DOI: 10.1016/j.asoc.2021.107355.
47. Kim D.Y., Han S.H., Kim H. et al. Structuring the prediction model of project performance for international construction projects: A comparative analysis. Expert systems with applications. 2009;36(2):1961–1971. DOI: 10.1016/j.eswa.2007.12.048.
48. Hussain S., Khan M.Q. Student-Performulator: Predicting Students Academic Performance at Secondary and Intermediate Level Using Machine Learning. Annals of data science. 2023;10(3):637–655. DOI: 10.1007/s40745–021–00341–0.
49. Martin A.J., Nejad H.G., Colmar S. et al. Adaptability: How students responses to uncertainty and novelty predict their academic and non-academic outcomes. Journal of Educational Psychology. 2013;105(3):728–746. DOI: 10.1037/a0032794.
50. Fernández-Martín F.D., Arco-Tirado J.L., Hervás-Torres M. Grit as a predictor and outcome of educational, professional and personal success: A systematic review. Psicología Educativa. 2020;26(2):163–173. DOI: 10.5093/psed2020a11.
51. Fedotova M.A. Artificial intelligence technologies in predicting the effectiveness of teamwork: experience, problems and prospects for practical research. Nauchnyi rezultat. Sotsiologiya i upravlenie = Scientific result. Sociology and management. 2019;5(2). (in Russ.). DOI: 10.18413/2408-9338-2019-5-2-0-9
52. Slavutskaya E.V., Slavutskii L.A. On the choice of the structure of artificial neural networks and algorithms for analyzing psychodiagnostic data. Kazanskii pedagogicheskii zhurnal = Kazan Pedagogical Journal. 2020;5(142):202–210. (in Russ.).
53. Petrov A.N., Ivanova G.F., Slavutskaya E.V. Training a neural network as a tool for system analysis of multidimensional psychodiagnostic data. Vestnik Chuvashskogo universiteta = Bulletin of the Chuvash University. 2018;1:162–168. (in Russ.).
54. Slavutskaya E.V., Abrukov V.S., Slavutskii L.A. Neural network system analysis of level psychological characteristics. Vestnik Chuvashskogo universiteta = Bulletin of the Chuvash University. 2016;1:164–173. (in Russ.).
55. Rastrollo-Guerrero J.L., Gómez-Pulido J.A., Durán-Domínguez A. Analyzing and Predicting Students Performance by Means of Machine Learning: A Review. Applied sciences. 2020;10(3). DOI: 10.3390/app10031042.
56. Namoun A., Alshanqiti A. Predicting Student Performance Using Data Mining and Learning Analytics Techniques: A Systematic Literature Review. Applied Sciences. 2021;11(1). DOI: 10.3390/app11010237.
References on translit
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Published
2023-12-31
How to Cite
Dmitrieva, Y., Korobova, S., & Gorskikh, A. (2023). Predicting students’ performance in project-based learning: a substantiation of an interdisciplinary study. Psychology. Psychophysiology, 16(4), 19-32. https://doi.org/10.14529/jpps230402
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Section
Methodological and theoretical issues of psychology
Copyright (c) 2023 Psychology. Psychophysiology
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