The influence of learning environment to students' non-cognitive outcomes: Looking through the PISA lens
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1 Emirates College for Advanced Education, Abu Dubai, UAE2 University of Bahrain, Zallaq, BAHRAIN3 Curtin University, Bentley, WA, AUSTRALIA* Corresponding Author
Abstract
To examine the relationship between students’ perceptions and their non-cognitive outcomes, this research uses secondary analysis of PISA data from 14,167 students in the United Arab Emirates. Seven factors of learning environment were identified after reviewing the literature. The findings reveal that six factors of the learning environments had a statistically significant association with epistemological beliefs. It was also found that three aspects of learning environments had a statistically significant association with self-efficacy. The results indicate that the three aspects of learning environments had a statistically significant association with anxiety. There was no association found between anxiety and any other teacher factors. The findings also show a positive and statistically significant relationship between students’ epistemological beliefs and self-efficacy, and a negative significant relationship between self-efficacy and anxiety. The research thus confirmed previous research by establishing a significant association between the nature of the learning environment and students’ cognitive outcomes.
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Article Type: Research Article
EURASIA J Math Sci Tech Ed, Volume 19, Issue 3, March 2023, Article No: em2233
https://doi.org/10.29333/ejmste/12967
Publication date: 01 Mar 2023
Online publication date: 17 Feb 2023
Article Views: 2138
Article Downloads: 1401
Open Access References How to cite this articleReferences
- Abdullah, M. Y., Hussin, S., & Shakir, M. (2018). The effect of peers’ and teacher’s e-feedback on writing anxiety level through CMC applications. International Journal of Emerging Technologies in Learning, 13(11), 196-207. https://doi.org/10.3991/ijet.v13i11.8448
- Agasisti, T., & Zoido, P. (2018). Comparing the efficiency of schools through international benchmarking: Results from an empirical analysis of OECD PISA 2012 data. Educational Researcher, 47(6), 352-362. https://doi.org/10.3102/0013189X18777495
- Aladejana, F., & Aderibigbe, O. (2007). Science laboratory environment and academic performance. Journal of Science Education and Technology, 16(6), 500-506. https://doi.org/10.1007/s10956-007-9072-4
- Aluri, V. L., & Fraser, B. J. (2019). Students’ perceptions of mathematics classroom learning environments: measurement and associations with achievement. Learning Environments Research, 22(3), 409-426. https://doi.org/10.1007/s10984-019-09282-1
- Amiryousefi, M., Amirian, Z., & Ansari, A. (2019). Relationship between classroom environment, teacher behavior, cognitive and emotional engagement, and state motivation. Journal of English language Teaching and Learning, 11(23), 27-59.
- Arbuckle, J. L. (2010). IBM SPSS AMOS TM 19 user’s guide. AMOS Development Corporation.
- Areepattamannil, S., Cairns, D., & Dickson, M. (2020). Teacher-directed versus inquiry-based science instruction: Investigating links to adolescent students’ science dispositions across 66 countries. Journal of Science Teacher Education, 31(6), 675-704. https://doi.org/10.1080/1046560X.2020.1753309
- Ashrafzade, T., Issazadegan, A., & Michaeeli Manee, F. (2019). Model causal relationship between epistemological beliefs and study skills on academic performance: The mediating role of academic self-efficacy. Educational Psychology, 15(53), 51-72. https://doi.org/10.22054/jep.2020.38743.2538
- Baird, J., Johnson, S., Hopfenbeck, T. N., Isaacs, T., Sprague, T., Stobart, G., & Yu, G. (2016). On the supranational spell of PISA in policy. Educational Research, 58(2), 121-138. https://doi.org/10.1080/00131881.2016.1165410
- Cai, J., Wen, Q., Lombaerts, K., Jaime, I., & Cai, L. (2022). Assessing students’ perceptions about classroom learning environments: The new what is happening in this class (NWIHIC) instrument. Learning Environments Research, 25(2), 601-618. https://doi.org/10.1007/s10984-021-09383-w
- Canpolat, A. M. (2019). The relationship between academic self-efficacy, learning styles and epistemological beliefs: A study on the students of the school of physical education and sports. Cypriot Journal of Educational Sciences, 14(4), 610-617. https://doi.org/10.18844/cjes.v11i4.4401
- Ceylan, E. (2020). Science teachers’ self-efficacy in instruction and self-efficacy in student engagement across Estonia, Japan, and Turkey. Journal of Education and Future, (18), 29-41. https://doi.org/10.30786/jef.751536
- Chi, S., Liu, X., Wang, Z., & Won Han, S. (2018). Moderation of the effects of scientific inquiry activities on low SES students’ PISA 2015 science achievement by school teacher support and disciplinary climate in science classroom across gender. International Journal of Science Education, 40(11), 1284-1304. https://doi.org/10.1080/09500693.2018.1476742
- Chi, S., Wang, Z., & Liu, X. (2021). Moderating effects of teacher feedback on the associations among inquiry-based science practices and students’ science-related attitudes and beliefs. International Journal of Science Education, 43(14), 2426-2456. https://doi.org/10.1080/09500693.2021.1968532
- Choi, S., Kusakabe, T., & Tanaka, Y. (2022). Enhancing non-cognitive skills by applying lesson study in lower secondary education: A project in Vietnam. Cogent Education, 9(1), 2082091. https://doi.org/10.1080/2331186X.2022.2082091
- Chong, W. H., Liem, G. A. D., Huan, V. S., Kit, P. L., & Ang, R. P. (2018). Student perceptions of self-efficacy and teacher support for learning in fostering youth competencies: Roles of affective and cognitive engagement. Journal of Adolescence, 68, 1-11. https://doi.org/10.1016/j.adolescence.2018.07.002
- Clark, K. R. (2018). Learning theories: Behaviorism. Radiologic Technology, 90(2), 172-175.
- Corbett, F., & Spinello, E. (2020). Connectivism and leadership: Harnessing a learning theory for the digital age to redefine leadership in the twenty-first century. Heliyon, 6(1), e03250. https://doi.org/10.1016/j.heliyon.2020.e03250
- Domínguez, M., Vieira, M.-J., & Vidal, J. (2012). The impact of the program for international student assessment on academic journals. Assessment in Education: Principles, Policy and Practice, 19(4), 393-409. https://doi.org/10.1080/0969594X.2012.659175
- Fetterly, J. M. (2020). Fostering mathematical creativity while impacting beliefs and anxiety in mathematics. Journal of Humanistic Mathematics, 10(2), 102-128. https://doi.org/10.5642/jhummath.202002.07
- Fornell, C., Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18, 39-50. https://doi.org/10.1177/002224378101800104
- Fraser, B. J. (1998). Classroom environment instruments: Development, validity, and applications. Learning Environments Research, 1, 7-33.
- Fraser, B. J. (2015). Classroom learning environments. In R. Gunstone (Ed.), Encyclopedia of science education (pp. 154-157). Springer. https://doi.org/10.1007/978-94-007-2150-0_186
- Gamazo, A., & Martínez-Abad, F. (2020). An exploration of factors linked to academic performance in PISA 2018 through data mining techniques. Frontiers in Psychology, 11, 575167. https://doi.org/10.3389/fpsyg.2020.575167
- Gardner, K., Glassmeyer, D., & Worthy, R. (2019). Impacts of STEM professional development on teachers’ knowledge, self-efficacy, and practice. Frontiers in Education, 4, 26. https://doi.org/10.3389/feduc.2019.00026
- Garner, S. L., Killingsworth, E., Bradshaw, M., Raj, L., Johnson, S. R., Abijah, S. P., Parimala, S., & Victor, S. (2018). The impact of simulation education on self‐efficacy towards teaching for nurse educators. International Nursing Review, 65(4), 586-595. https://doi.org/10.1111/inr.12455
- Gielnik, M. M., Bledow, R., & Stark, M. S. (2020). A dynamic account of self-efficacy in entrepreneurship. Journal of Applied Psychology, 105(5), 487. https://doi.org/10.1037/apl0000451
- Goodnough, K. (2018). Addressing contradictions in teachers’ practice through professional learning: An activity theory perspective. International Journal of Science Education, 40(17), 2181-2204. https://doi.org/10.1080/09500693.2018.1525507
- Govorova, E., Benítez, I., & Muñiz, J. (2020). Predicting student well-being: Network analysis based on PISA 2018. International Journal of Environmental Research and Public Health, 17(11), 4014. https://doi.org/10.3390/ijerph17114014
- Grabau, L. J., Lavonen, J., & Juuti, K. (2021). Finland, a package deal: Disciplinary climate in science classes, science dispositions and science literacy. Sustainability, 13(24), 13857. https://doi.org/10.3390/su132413857
- Graham, J. W. (2012). Missing data: Analysis and design. Springer. https://doi.org/10.1007/978-1-4614-4018-5
- Gunes, G., & Bati, K. (2018). Development of a scale on scientific epistemological views and investigation of epistemological views of prospective teachers. International Journal of Research in Education and Science, 4(2), 391-408. https://doi.org/10.21890/ijres.409299
- Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1992). Multivariate data analysis with readings. MacMillan.
- Han, J., Geng, X., & Wang, Q. (2021). Sustainable development of university EFL learners’ engagement, satisfaction, and self-efficacy in online learning environments: Chinese experiences. Sustainability, 13(21), 11655. https://doi.org/10.3390/su132111655
- Händel, M., Stephan, M., Gläser-Zikuda, M., Kopp, B., Bedenlier, S., & Ziegler, A. (2020). Digital readiness and its effects on higher education students’ socio-emotional perceptions in the context of the COVID-19 pandemic. Journal of Research on Technology in Education, 54(2), 267-280. https://doi.org/10.1080/15391523.2020.1846147
- Harrington, D. (2009). Confirmatory factor analysis. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780195339888.001.0001
- Ichsan, I. Z., Sigit, D. V., & Miarsyah, M. (2019). Environmental learning based on higher order thinking skills: A needs assessment. International Journal for Educational and Vocational Studies, 1(1), 21-24. https://doi.org/10.29103/ijevs.v1i1.1389
- Jin, Y. (2022). The promoting effect of mental health education on students’ social adaptability: Implications for environmental. Journal of Environmental and Public Health, 2022, 1607456. https://doi.org/10.1155/2022/1607456
- Jin, Y. X., & Dewaele, J. M. (2018). The effect of positive orientation and perceived social support on foreign language classroom anxiety. System, 74, 149-157. https://doi.org/10.1016/j.system.2018.01.002
- Johnson, E. S., Clohessy, A. B., & Chakravarthy, P. (2021). A self-regulated learner framework for students with learning disabilities and math anxiety. Intervention in School and Clinic, 56(3), 163-171. https://doi.org/10.1177/1053451220942203
- Karakolidis, A., Pitsia, V., & Emvalotis, A. (2019). The case of high motivation and low achievement in science: What is the role of students’ epistemic beliefs? International Journal of Science Education, 41(11), 1457-1474. https://doi.org/10.1080/09500693.2019.1612121
- Khine, M. S., Fraser, B. J., & Afari, E. (2020). Structural relationships between learning environments and students’ non-cognitive outcomes: Secondary analysis of PISA data. Learning Environments Research, 23(3), 395-412. https://doi.org/10.1007/s10984-020-09313-2
- Kline, R. B. (2011). Principles and practices of structural equation modeling. Guilford Press.
- Kolil, V. K., Muthupalani, S., & Achuthan, K. (2020). Virtual experimental platforms in chemistry laboratory education and its impact on experimental self-efficacy. International Journal of Educational Technology in Higher Education, 17(1), 1-22. https://doi.org/10.1186/s41239-020-00204-3
- Lazarides, R., & Buchholz, J. (2019). Student-perceived teaching quality: How is it related to different achievement emotions in mathematics classrooms? Learning and Instruction, 61, 45-59. https://doi.org/10.1016/j.learninstruc.2019.01.001
- Lee, J., Park, T., & Davis, R. O. (2022). What affects learner engagement in flipped learning and what predicts its outcomes? British Journal of Educational Technology, 53(2), 211-228. https://doi.org/10.1111/bjet.12717
- Lee, M.-H., Liang, J.-C., Wu, Y.-T., Chiou, G.-L., Hsu, C.-Y., Wang, C.-Y., Lin, J.-W., & Tsai, C.-C. (2020). High school students’ conceptions of science laboratory learning, perceptions of the science laboratory environment, and academic self-efficacy in science learning. International Journal of Science and Mathematics Education, 18(1), 1-18. https://doi.org/10.1007/s10763-019-09951-w
- Lei, H., Cui, Y., & Chiu, M. M. (2018). The relationship between teacher support and students’ academic emotions: A meta-analysis. Frontiers in Psychology, 8, 2288. https://doi.org/10.3389/fpsyg.2017.02288
- Lin, T. J., Deng, F., Chai, C. S., & Tsai, C. C. (2013). High school students’ scientific epistemological beliefs, motivation in learning science, and their relationships: A comparative study within the Chinese culture. International Journal of Educational Development, 33(1), 37-47. https://doi.org/10.1016/j.ijedudev.2012.01.007
- Lindblad, S., Pettersson, D., & Popkewitz, T. S. (2015). International comparisons of school results: A systematic review of research on large scale assessments in education. Swedish Research Council.
- Liu, X. X., Gong, S. Y., Zhang, H. P., Yu, Q. L., & Zhou, Z. J. (2021). Perceived teacher support and creative self-efficacy: The mediating roles of autonomous motivation and achievement emotions in Chinese junior high school students. Thinking Skills and Creativity, 39, 100752. https://doi.org/10.1016/j.tsc.2020.100752
- Maison, S., & Syamsurizal, T. (2019). Learning environment, students’ beliefs, and self-regulation in learning physics: Structural equation modeling. Journal of Baltic Science Education, 18(3), 389. https://doi.org/10.33225/jbse/19.18.389
- Malik, R. H., & Rizvi, A. A. (2018). Effect of classroom learning environment on students’ academic achievement in mathematics at secondary level. Bulletin of Education and Research, 40(2), 207-218.
- Mammadov, R., & Cimen, I. (2019). Optimizing teacher quality based on student performance: A data envelopment analysis on PISA and TALIS. International Journal of Instruction, 12(4), 767-788. https://doi.org/10.29333/iji.2019.12449a
- McMinn, M., & Aldridge, J. (2020). Learning environment and anxiety for learning and teaching mathematics among preservice teachers. Learning Environments Research, 23(3), 331-345. https://doi.org/10.1007/s10984-019-09304-y
- MOE. (2018). PISA 2018. Ministry of Education. https://www.moe.gov.ae/En/ImportantLinks/InternationalAssessments/Documents/PISA/Brochure.pdf
- Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory. McGraw-Hill.
- Nurhidayat, N., Jariono, G., Sudarmanto, E., Kurniawan, A. T., Triadi, C., & Anisa, M. N. (2021). Teacher strategy in reducing hyperactive behavior of children with special needs during pandemic COVID-19 at SLBN Sukoharjo. International Journal of Economy, Education and Entrepreneurship, 1(1), 79-86. https://doi.org/10.53067/ije3.v1i1.13
- OECD. (2017). PISA 2015 technical report. OECD. https://www.oecd.org/pisa/data/2015-technical-report/
- OECD. (2019). Trends shaping education 2019. OECD Publishing.
- Oliver, M., McConney, A., & Woods-McConney, A. (2021). The efficacy of inquiry-based instruction in science: A comparative analysis of six countries using PISA 2015. Research in Science Education, 51(2), 595-616. https://doi.org/10.1007/s11165-019-09901-0
- Pamuk, S., Sungur, S., & Oztekin, C. (2017). A multilevel analysis of students’ science achievements in relation to their self-regulation, epistemological beliefs, learning environment perceptions, and teachers’ personal characteristics. International Journal of Science and Mathematics Education, 15(8), 1423-1440. https://doi.org/10.1007/s10763-016-9761-7
- Patkin, D., & Greenstein, Y. (2020). Mathematics anxiety and mathematics teaching anxiety of in-service and pre-service primary school teachers. Teacher Development, 24(4), 502-519. https://doi.org/10.1080/13664530.2020.1785541
- Peffer, M. E., & Ramezani, N. (2019). Assessing epistemological beliefs of experts and novices via practices in authentic science inquiry. International Journal of STEM Education, 6(1), 1-23. https://doi.org/10.1186/s40594-018-0157-9
- Pennings, H. J., Brekelmans, M., Sadler, P., Claessens, L. C., van der Want, A. C., & van Tartwijk, J. (2018). Interpersonal adaptation in teacher-student interaction. Learning and Instruction, 55, 41-57. https://doi.org/10.1016/j.learninstruc.2017.09.005
- Rabei, S., Ramadan, S., & Abdallah, N. (2020). Self-efficacy and future anxiety among students of nursing and education colleges of Helwan University. Middle East Current Psychiatry, 27(1), 1-5. https://doi.org/10.1186/s43045-020-00049-6
- Radišić, J., Videnović, M., & Baucal, A. (2018). Distinguishing successful students in mathematics-A comparison across European countries. Psihologija [Psychology], 51(1), 69-89. https://doi.org/10.2298/PSI170522019R
- Rahmiati, I. I., & Emaliana, I. (2020). EFL students’ online learning: Epistemic beliefs determine learning strategies. EDUCAFL: Journal of Education of English as Foreign Language, 2(2), 87-97. https://doi.org/10.21776/ub.Educafl.2019.002.02.05
- Rongen, F., McKenna, J., Cobley, S., Tee, J. C., & Till, K. (2020). Psychosocial outcomes associated with soccer academy involvement: Longitudinal comparisons against aged matched school pupils. Journal of Sports Sciences, 38(11-12), 1387-1398. https://doi.org/10.1080/02640414.2020.1778354
- Rosen, D. J., & Kelly, A. M. (2020). Epistemology, socialization, help seeking, and gender-based views in in-person and online, hands-on undergraduate physics laboratories. Physical Review Physics Education Research, 16(2), 020116. https://doi.org/10.1103/PhysRevPhysEducRes.16.020116
- Rubin, D. B. (1996). Multiple imputation after 18+ years (with discussion). Journal of the American Statistical Association, 91, 473-489. https://doi.org/10.1080/01621459.1996.10476908
- Ruegg, R. (2018). The effect of peer and teacher feedback on changes in EFL students’ writing self-efficacy. The Language Learning Journal, 46(2), 87-102. https://doi.org/10.1080/09571736.2014.958190
- Savitsky, B., Findling, Y., Ereli, A., & Hendel, T. (2020). Anxiety and coping strategies among nursing students during the COVID-19 pandemic. Nurse Education in Practice, 46, 102809. https://doi.org/10.1016/j.nepr.2020.102809
- Schafer, J. L., & Graham, J. W. (2002). Missing data: Our view of the state of the art. Psychological Methods, 7, 147-177. https://doi.org/10.1037/1082-989X.7.2.147
- Schommer, M. (2019). An emerging conceptualization of epistemological beliefs and their role in learning. In R. Garner, & P. A. Alexander (Eds.), Beliefs about text and instruction with text (pp. 25-40). Routledge. https://doi.org/10.4324/9780203812068-2
- Sengul, O., Enderle, P. J., & Schwartz, R. S. (2020). Science teachers’ use of argumentation instructional model: Linking PCK of argumentation, epistemological beliefs, and practice. International Journal of Science Education, 42(7), 1068-1086. https://doi.org/10.1080/09500693.2020.1748250
- Skordi, P., & Fraser, B. J. (2019). Validity and use of the what is happening in this class? (WIHIC) questionnaire in university business statistics classrooms. Learning Environments Research, 22(2), 275-295. https://doi.org/10.1007/s10984-018-09277-4
- Stormon, N., Ford, P. J., Kisely, S., Bartle, E., & Eley, D. S. (2019). Depression, anxiety and stress in a cohort of Australian dentistry students. European Journal of Dental Education, 23(4), 507-514. https://doi.org/10.1111/eje.12459
- Tahmassian, K., & Moghadam, N. J. (2011). Relationship between self-efficacy and symptoms of anxiety, depression, worry and social avoidance in a normal sample of students. Iranian Journal of Psychiatry and Behavioral Sciences, 5(2), 91.
- Teig, N., Scherer, R., & Nilsen, T. (2019). I know I can, but do I have the time? The role of teachers’ self-efficacy and perceived time constraints in implementing cognitive-activation strategies in science. Frontiers in Psychology, 10, 1697. https://doi.org/10.3389/fpsyg.2019.01697
- Teo, T. (2009). Modelling technology acceptance in education: A study of pre-service teachers. Computers & Education, 52(2), 302-312. https://doi.org/10.1016/j.compedu.2008.08.006
- Teo, T. (2010). The development, validation, and analysis of measurement invariance of the technology acceptance measure for preservice teachers (TAMPST). Educational and Psychological Measurement, 70(6), 990-1006. https://doi.org/10.1177/0013164410378087
- Torres, J. T., Strong, Z. H., & Adesope, O. O. (2020). Reflection through assessment: A systematic narrative review of teacher feedback and student self-perception. Studies in Educational Evaluation, 64, 100814. https://doi.org/10.1016/j.stueduc.2019.100814
- Ucar, F. M. (2018). Investigation of gifted students’ epistemological beliefs, self-efficacy beliefs and use of metacognition. Journal for the Education of Gifted Young Scientists, 6(3), 1-10. https://doi.org/10.17478/JEGYS.2018.77
- Vanbecelaere, S., Van den Berghe, K., Cornillie, F., Sasanguie, D., Reynvoet, B., & Depaepe, F. (2020). The effects of two digital educational games on cognitive and non-cognitive math and reading outcomes. Computers & Education, 143, 103680. https://doi.org/10.1016/j.compedu.2019.103680
- Varanasi, R. A., Vashistha, A., Parikh, T., & Dell, N. (2020). Challenges and issues integrating smartphones into teacher support programs in India. In Proceedings of the 2020 International Conference on Information and Communication Technologies and Development (pp. 1-11). https://doi.org/10.1145/3392561.3394638
- Walsh, P., Owen, P. A., Mustafa, N., & Beech, R. (2020). Learning and teaching approaches promoting resilience in student nurses: An integrated review of the literature. Nurse Education in Practice, 45, 102748. https://doi.org/10.1016/j.nepr.2020.102748
- Wang, X., Liu, Y. L., Ying, B., & Lin, J. (2021). The effect of learning adaptability on Chinese middle school students’ English academic engagement: The chain mediating roles of foreign language anxiety and English learning self-efficacy. Current Psychology. https://doi.org/10.1007/s12144-021-02008-8
- Wang, Y. L., Liang, J. C., & Tsai, C. C. (2018). Cross-cultural comparisons of university students’ science learning self-efficacy: Structural relationships among factors within science learning self-efficacy. International Journal of Science Education, 40(6), 579-594. https://doi.org/10.1080/09500693.2017.1315780
- Wang, Y., Wang, R., & Lu, J. (2022). Exploring the impact of university student engagement on junior faculty’s online teaching anxiety and coping strategies during COVID-19. Education Sciences, 12(10), 664. https://doi.org/10.3390/educsci12100664
- Yang, J. C., & Quadir, B. (2018). Effects of prior knowledge on learning performance and anxiety in an English learning online role-playing game. Journal of Educational Technology & Society, 21(3), 174-185. http://www.jstor.org/stable/26458516
- Yerdelen, S., & Sungur, S. (2019). Multilevel investigation of students’ self-regulation processes in learning science: Classroom learning environment and teacher effectiveness. International Journal of Science and Mathematics Education, 17(1), 89-110. https://doi.org/10.1007/s10763-018-9921-z
- Yin, H., Shi, L., Tam, W. W. Y., & Lu, G. (2020). Linking university mathematics classroom environments to student achievement: The mediation of mathematics beliefs. Studies in Educational Evaluation, 66, 100905. https://doi.org/10.1016/j.stueduc.2020.100905
- Yorke, L., Rose, P., Bayley, S., Wole, D., & Ramchandani, P. (2021). The importance of students’ socio-emotional learning, mental health and wellbeing in the time of COVID-19. RISE. https://doi.org/10.35489/BSG-RISE-RI_2021/025
How to cite this article
APA
Ali, N., Abu Khurma, O., Afari, E., & Swe Khine, M. (2023). The influence of learning environment to students' non-cognitive outcomes: Looking through the PISA lens. Eurasia Journal of Mathematics, Science and Technology Education, 19(3), em2233. https://doi.org/10.29333/ejmste/12967
Vancouver
Ali N, Abu Khurma O, Afari E, Swe Khine M. The influence of learning environment to students' non-cognitive outcomes: Looking through the PISA lens. EURASIA J Math Sci Tech Ed. 2023;19(3):em2233. https://doi.org/10.29333/ejmste/12967
AMA
Ali N, Abu Khurma O, Afari E, Swe Khine M. The influence of learning environment to students' non-cognitive outcomes: Looking through the PISA lens. EURASIA J Math Sci Tech Ed. 2023;19(3), em2233. https://doi.org/10.29333/ejmste/12967
Chicago
Ali, Nagla, Othman Abu Khurma, Ernest Afari, and Myint Swe Khine. "The influence of learning environment to students' non-cognitive outcomes: Looking through the PISA lens". Eurasia Journal of Mathematics, Science and Technology Education 2023 19 no. 3 (2023): em2233. https://doi.org/10.29333/ejmste/12967
Harvard
Ali, N., Abu Khurma, O., Afari, E., and Swe Khine, M. (2023). The influence of learning environment to students' non-cognitive outcomes: Looking through the PISA lens. Eurasia Journal of Mathematics, Science and Technology Education, 19(3), em2233. https://doi.org/10.29333/ejmste/12967
MLA
Ali, Nagla et al. "The influence of learning environment to students' non-cognitive outcomes: Looking through the PISA lens". Eurasia Journal of Mathematics, Science and Technology Education, vol. 19, no. 3, 2023, em2233. https://doi.org/10.29333/ejmste/12967