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999			_c21963 _d21963
003			OSt
005			20241219111327.0
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040			_aAIKTC-KRRC _cAIKTC-KRRC
100			_924871 _aChakraborty, R.
245			_aConfigural measurement equivalence testing of the comprehensive trait based model of self-regulated learning in engineering undergraduates
250			_aVol.37(3), Jan
260			_aSangli _bK.E. Society's Rajarambapu Institute of Technology _c2024
300			_a143-156p.
520			_aThe present study extended the integrative trait model of self regulated learning by [30] by including the remaining behavioral and emotional components. Measurement invariance testing was conducted to check for the equivalence of the model with respect to gender, stream and batch among 488 (351 male and 137 female; 321 Computer Science and 167 Mechanical; 263 IInd Year and 225 IIIrd Year) engineering students selected through stratified random sampling from the three regions, Majha, Doaba and Malwa, of the Punjab state of India. [25] measurement invariance criterion of ΔCFI be less than or equal to 0.01 was used to test for equivalence of the model across the selected groups, since it is unaffected by model complexity, sample size and unrelated to overall fit measures. The revised integrative trait model of self regulated learning among engineering undergraduates was found to be Configural measurement invariant with respect to gender, stream and batch using SPSS Amos Ver. 23.0, meaning that the construct of self regulated learning is conceptualized by the participants across the groups of the study in same way. Reliability of the instrument's 14 variables was estimated using Pearson's correlation-based Cronbach's alpha (using SPSS Statistics Ver. 23.0) and Polychoric correlation based ordinal alpha (using R Package Psych), along with estimation of attenuation index to show the extent of underestimation of the vital psychometric property by assuming the data of Likert scale based questionnaires as continuous interval and on ignoring its categorical ordinal nature. The effect size of the validated model conducted as part of post-hoc power analysis using semPower R package was found to be satisfactorily high at 0.941. The academic implications of the study with respect to engineering education in the country are discussed.
650		0	_94642 _aHumanities and Applied Sciences
700			_924872 _aChechi, V. K.
773	0		_x2349-2473 _tJournal of engineering education transformations (JEET) _dSangli Rajarambapu Institute Of Technology
856			_uhttps://journaleet.in/articles/configural-measurement-equivalence-testing-of-the-comprehensive-trait-based-model-of-self-regulated-learning-in-engineering-undergraduates _yClick here
942			_2ddc _cAR