000			03286ntm a2200313 i 4500
003			MY-KuUP
005			20260407144038.0
006			t||||fr|||| 000 0
007			ta
008			260407t20252025my a|||fr|||| 000 0 eng d
020			_aTHE0010443 (Local) _qHardback
040			_aUMPSA _beng _cUMPSA _erda
090			_aPSK .B6 2025 r Thesis
100	0		_aPan, Bo, _eauthor.
245	1	0	_aExploring factors influencing deep learning among teacher education students in spoc blended learning : _ba case study of hebei minzu normal university / _cPan Bo
300			_axix, 364 pages : _billustrations (some color) ; _c30 cm. + _e1 CD-ROM
336			_2rdacontent _atext
337			_2rdamedia _aunmediated
338			_2rdacarrier _avolume
347			_2rda _atext file _bPDF
500			_aCentre for Human Sciences
502			_aThesis (Doctor of Philosophy) -- Universiti Malaysia Pahang - 2025
504			_aIncludes bibliographical references
520	3		_aThe cultivation quality of teacher education students directly affects educational equity, cultural transmission, and sustainable development. Deep learning is essential for enhancing their knowledge transfer, application, and critical thinking, thus serving as a key driver of professional development. With the advancement of educational technology, SPOC (Small Private Online Course) blended learning provides a flexible and personalized environment that supports teaching quality and fosters deep learning. Despite its importance, existing research often remains at the macro level and lacks empirical studies that consider the specific developmental characteristics of teacher education students, especially regarding student engagement, knowledge transfer and application, and critical thinking. To address this gap, the present study integrates humanistic learning theory and the Constructivist Learning Environment (CLE) framework, adopting a quantitative design that combines interviews with 13 teachers and survey data from 685 students. Through this approach, the study identifies and validates the key factors influencing deep learning in SPOC environments and develops the SC–TC–EES–TR model, which incorporates Student Competence (SC), Teacher Competence (TC), Educational Ecosystem Support (EES), and Teaching Resources (TR). Findings reveal that student competence has significant direct effects on all dimensions of deep learning, while teacher competence influences outcomes indirectly through students, resources, and ecosystem support. Teaching resources exert positive effects via student competence, and ecosystem support plays a crucial role in knowledge transfer and application. Additional factors, such as learning motivation, platform use, and teaching motivation, also shape outcomes in specific dimensions. This study contributes to clarifying the mechanisms of deep learning in SPOC blended learning, enriches the theoretical framework of deep and blended learning, and provides practical implications for instructional design, resource optimization, and the cultivation of high-quality teacher education students.
610	2	0	_aCentre for Human Sciences _xDissertations
650		0	_aUniversities and colleges _xDissertations
650		0	_aTheses _xDissertations
942			_2lcc _cTHESIS
999			_c104645 _d104651