Razvoj in validacija kompetenčnega profila za poučevanje in učenje raziskovalne integritete
Povzetek
Ker raziskovalna integriteta ni nekaj ločenega od raziskovanja, ampak njen sestavni del, jo je treba vključiti v usposabljanje na področju raziskovanja. Obstaja pa več ovir v povezavi s sodobnim izobraževanjem o raziskovalni integriteti. Da bi jih odpravili, smo razvili kompetenčni profil za poučevanje in učenje raziskovalne integritete, ki temelji na štirih predpostavkah: 1) vključiti vse stopnje študija (dodiplomski, magistrski in doktorski študij); 2) vključiti raziskovalno integriteto v raziskovanje; 3) obravnavati vprašanja raziskovalne integritete v kontekstualno specifičnih praksah; 4) posebno pozornost nameniti »sivi coni« ali spornim raziskovalnim praksam. Da bi ocenili veljavnost vsebine kompetenčnega profila in ugotovili, ali so potrebne njegove prilagoditve, smo kompetence v profilu prevedli v postavke merilnega instrumenta (vprašalnika) in izvedli raziskavo med študenti Univerze v Ljubljani. Raziskava nam je omogočila naslednje: 1) pridobiti informacije o odnosu študentov do vprašanj raziskovalne integritete; 2) analizirati razlike v tem odnosu med študenti dodiplomskega, magistrskega in doktorskega študija; 3) statistično potrditi kompetenčni profil in predlagati morebitne izboljšave. Rezultati so pokazali naslednje: 1) študentje se zelo dobro zavedajo vprašanj raziskovalne integritete, saj so pri vseh ocenjenih postavkah dosegli visoke rezultate. Kljub temu je bilo nekaj odstopanj pri nižjih ocenah, zlasti v povezavi z vprašljivimi raziskovalnimi praksami, kar potrjuje našo domnevo, da so vprašanja »sive cone« tista, ki jih je treba v sodobnem izobraževanju o raziskovalni integriteti še posebej obravnavati in jim nameniti posebno pozornost; 2) razlike v stališčih študentov dodiplomskega, magistrskega in doktorskega študija so pokazale, da so se študentje višje stopnje bistveno bolj zavedali vprašanj integritete kot študentje nižje stopnje, kar nakazuje, da bi bilo treba vprašanjem raziskovalne integritete nameniti posebno pozornost že na ravni dodiplomskega študija; 3) merske značilnosti so pokazale, da je bila zanesljivost vprašalnika zelo visoka, kar kaže na dobro splošno strukturo kompetenčnega profila. Tudi analiza glavnih komponent je potrdila strukturo kompetenčnega profila (vrednote in načela, raziskovalna praksa, objava in razširjanje ter kršitve). Analiza pa je pokazala tudi, da se podstruktura štirih glavnih področij profila ni povsem ujemala z rezultati faktorske analize, kar kaže, da bi bilo treba ponovno razmisliti o razporeditvi kompetenc v kompetenčnem profilu, zlasti na področju raziskovalne prakse. Nedavni razvoj na področju raziskovalne integritete prav tako kaže, da bi bilo treba kompetenčni profil posodobiti z vprašanji glede vpliva umetne inteligence na raziskovalno integriteto.Prenosi
Literatura
Alemu, S. K. (2020). Transnational mobility of academics: Some academic impacts. Center for Educational Policy Studies Journal, 10(2), 77–99. https://doi.org/10.26529/cepsj.464
Antes A., & DuBois J. M. (2014). Aligning objectives and assessment in responsible conduct of research instruction. Journal of Microbiology & Biology Education, 15(2), 108–116. https://doi.org/10.1128/jmbe.v15i2.852
Bebeau, M. J. (2002a). Influencing the moral dimensions of professional practice: Implications for teaching and assessing for research integrity. In N. A., Steneck, & M. H. Sheetz (Eds.), Proceedings of the first ORI research conference on research integrity (pp. 179–187). Office of Research Integrity, Department of Health and Human Services. https://ori.hhs.gov/documents/proceedings_rri.pdf
Bebeau, M. J. (2002b). The defining issues test and the four component model: Contributions to professional education. Journal of Moral Education, 31(3), 271–295. https://doi.org/10.1080/0305724022000008115
Bebeau, M. J. (2002c). Outcome measures for assessing integrity in the research environment (Appendix B). In US National Research Council. Integrity in scientific research: Creating an environment that promotes responsible conduct (pp. 143-166). The National Academies Press. https://www.nap.edu/read/10430/chapter/11
Bebeau, M. J., & Thoma, S. J. (1999). Intermediate concepts and the connection to moral education. Educational Psychology Review, 11(4), 343–360. https://doi.org/10.1023/A:1022057316180
Bison, R. (2023, July 19). Rise of AI stokes fears research misconduct could accelerate. Research Professional News. https://www.researchprofessionalnews.com/rr-news-world-2023-7-rise-of-aistokes-fears-research-misconduct-could-accelerate/
Böttcher, F., & Thiel, F. (2018), Evaluating research-oriented teaching: A new instrument to assess university students' research competences. Higher Education, 75(1), 91–110. https://doi.org/10.1007/s10734-017-0128-y
Brent, T. (2023, June 27). European research integrity code updated to reflect advances in artificial intelligence. Science Business. https://sciencebusiness.net/news/AI/european-research-integritycode-updated-reflect-advances-artificial-intelligence
Butler, N., Delaney. H., & Spoelstra S. (2017). The gray zone: questionable research practices in the business school. Academy of Management Learning & Education, 16(1), 94–109. https://doi.org/10.5465/amle.2015.0201
Council of Europe (2023, April 26). EduTalks@Council of Europe – Artificial Intelligence and Academic Integrity. Council of Europe. https://www.coe.int/en/web/education/-/edutalks-council-of-europe-artificial-intelligence-andacademic-integrity
Currie, G. M. (2023). Academic integrity and artificial intelligence: is ChatGPT hype, hero or heresy? Seminars in Nuclear Medicine, 53(5), 719–730. https://doi.org/10.1053/j.semnuclmed.2023.04.008
Davis, M., & Feinerman A. (2010). Assessing graduate student progress in engineering ethics. Science and Engineering Ethics, 18(2), 351–367. https://doi.org/10.1007/s11948-010-9250-2
Davis, M., & Riley K. (2008). Ethics across the graduate engineering curriculum: An experiment in teaching and assessment. Teaching Ethics, 9(1), 25–42. https://doi.org/10.5840/tej20089115
Dawson, A. G. (2023). Artificial intelligence and academic integrity. Aspen Publishing.
Diaz-Martinez, L. A., Fisher, G. R., Esparza, D., Bhatt, J. M., D'Arcy, C. E., Apodaca, J., Brownell, S., Corwin, L., Davis, W. B., Floyd, K. W., Killion, P. J., Madden, J., Marsteller, P., Mayfield-Meyer, T., McDonald, K. K., Rosenberg, M., Yarborough, M. A., & Olimpo, J. T. (2019). Recommendations for effective integration of ethics and responsible conduct of research (E/RCR) education into coursebased undergraduate research experiences: A meeting report. CBE–Life Sciences Education, 18(2), 1–10. https://doi.org/10.1187/cbe.18-10-0203
Eaton, S. E. (2023, March 4). Artificial intelligence and academic integrity, post-plagiarism. University World News. https://www.universityworldnews.com/post.php?story=20230228133041549
Eke, D. O. (2023). ChatGPT and the rise of generative AI: Threat to academic integrity? Journal of Responsible Technology, 13. https://doi.org/10.1016/j.jrt.2023.100060
Fanelli, D. (2013). Redefine misconduct as distorted reporting. Nature, 494(7436), 149. https://doi.org/10.1038/494149a
Gonzáles J., & Wagenaar R. (Eds.) (2008). Universities' contribution to the Bologna Process: An introduction (2nd Edition). Universidad de Deusto. https://www.unideusto.org/tuningeu/publications/278-universitiesacontribution-to-the-bolognaprocess-an-introduction-english-version.html
Hall, J., & Martin, B. R. (2019). Towards a taxonomy of research misconduct: The case of business school research. Research Policy, 48(2), 414–427. https://doi.org/10.1016/j.respol.2018.03.006
Hauser, F., Reuter, R., Gruber, H., & Mottok, J. (2018). Research competence: Modification of a questionnaire to measure research competence at universities of applied sciences. In C. S. Gonzáles Gonzáles, M. Castro & M. Llamas Nistal (Eds.), Proceedings of 2018 IEEE Global Engineering Education Conference (EDUCON 2018) (pp. 109–117). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/EDUCON.2018.8363216
Hussain, M. M. (2023). The policy efforts to address racism and discrimination in higher education institutions: the case of Canada. Center for Educational Policy Studies Journal, 13(2), 9–29. https://doi.org/10.26529/cepsj.965
Kohlberg, L. (1969). Stage and sequence: The cognitive development approach to socialization. In D. A. Goslin (Ed.), Handbook of socialization theory (pp. 347–480). Rand McNally.
Kohlberg, L. (1976). Moral stages and moralization: The cognitive-developmental. In T. Lickona (Ed.), Moral development and behavior: Theory, research and social issues (pp. 31–53). Holt, Rinehart and Winston.
LinkedIn (2023, August 3). What are some best practices for validating and updating competency models? https://www.linkedin.com/advice/0/what-some-best-practices-validating-updating-1e
Nanda, N. (2021, December 7). Is artificial intelligence a threat to academic integrity? Original by Turnitin. https://www.ouriginal.com/is-ai-a-threat-to-academic-integrity/
NPA Core Competencies Committee (2007-2009). The NPA postdoctoral core competencies. https://www.nationalpostdoc.org/page/CoreCompetencies
OECD Future of Education and Skills 2030 (2019). OECD learning compass 2030: A series of concept notes. http://www.oecd.org/education/2030-project/teaching-and-learning/learning/learningcompass-2030/OECD_Learning_Compass_2030_Concept_Note_Series.pdf
Olatunde Oduoye, M., Javed, B., Gupta, N., & Valentina Sih, C. M. (2023). Algorithmic Bias and Research integrity; the role of non-human authors in shaping scientific knowledge with respect to Artificial Intelligence (AI); a perspective. International Journal of Surgery. Advance online publication. https://doi.org/10.1097/JS9.0000000000000552
Rest, J. (1983). Morality. In P. H. Mussen, J. Flavell, and E. Markman (Eds.), Handbook of Child Psychology, Vol. 3, Cognitive Development (4th ed.) (pp. 556–629). Wiley.
Schaper, N. (2017). Why is it necessary to validate models of pedagogical competency? GMS Journal for Medical Education, 34(4), 1–8. https://doi.org/10.3205/zma00112
Selan, J., Metljak, M., Berčnik, S., & Dagarin Fojkar, M. (2021). Competency profile for teaching and learning research integrity. Faculty of Education University of Ljubljana. https://zalozba.pef.uni-lj.si/index.php/zalozba/catalog/book/176
Steneck, N. (2006). Fostering integrity in research: Definition, current knowledge, and future directions. Science and Engineering Ethics, 12(1), 53–74. https://doi.org/10.1007/PL00022268
The European Centre for the Development of Vocational Training (Cedefop) (2011). Glossary: Quality in education and training. Publications Office of the European Union. https://www.cedefop.europa.eu/files/4106_en.pdf
The Ohio State University (2023, April 6). Artificial intelligence and academic integrity. The Ohio State University. https://oaa.osu.edu/artificial-intelligence-and-academic-integrity
The US National Academies of Sciences, Engineering, and Medicine (2017). Fostering integrity in research. The National Academies Press. https://doi.org/10.17226/21896
The US National Research Council (2002). Integrity in scientific research: Creating an environment that promotes responsible conduct. The National Academies Press. https://doi.org/10.17226/10430
Trachtenberg, B. (2023). ChatGPT, artificial intelligence, and academic integrity. Office of Academic Integrity. University of Missouri. https://oai.missouri.edu/chatgpt-artificial-intelligence-and-academic-integrity/
Turnitin. (2023). Academic integrity in the age of AI. Turnitin. https://www.turnitin.com/resources/academic-integrity-in-the-age-of-AI
University of Cambridge (2023). Artificial Intelligence. University of Cambridge. https://www.plagiarism.admin.cam.ac.uk/what-academic-misconduct/artificial-intelligence
York University (2023, August 16). AI technology and academic integrity for instructors. York University. https://www.yorku.ca/unit/vpacad/academic-integrity/ai-technology-and-academic-integrity/
Zobel, J. (2023, May 19). We need to retain research integrity in the AI era. Pursuit and Research, University of Melbourne. https://pursuit.unimelb.edu.au/articles/we-need-to-retain-research-integrity-in-the-ai-era
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