Special Support for Successful Project Management in Higher Education Fields in Technology and Business Higher Education

Proceedings of The 6th International Conference on Future of Teaching and Education

Year: 2022



Special Support for Successful Project Management in Higher Education Fields in Technology and Business Higher Education

M.A.(ed.) Janne Heilala



The study reports a retrospective view of higher education undergraduate learning experiences to develop a pedagogical culture compliant with Learning-to-Learn (L2L). The reference sample consists of students in the technology and business fields (n = 76). The study utilizes pre-clinically captured Special Support of Motivation (SSM) for identifying L2L in the Project Management (PM) context by establishing a Questionnaire (SSM4L2LPMQ) in students’ self-responses on assessment of themselves which is constructed over 11-core character arguments (3 per se) concerning the existing collection of SSM4L2LPMQ framework model fit indices for reflection on Student Observations of Teachers in University (SOTU) 2-core elements (per se). The core key elements are well-known L2L arguments, combining popular educational psychology psychometric measures. The aim is to evaluate SSM4L2LPMQ’s reliability and validity and discuss its results. Piloted outcomes provide a comforting fit for psychological coherence, invariance measurement, and test reliability. SSM4L2LPMQ is one of the greatest reasons education for different context-specific topics fails. The instrument has been used a few times in SSM measures routinely in publications; validated, published, and discussed; this modified SSM4L2LPMQ’s potential is a crucial question battery for large-scale SSM features that helps teachers to face special student requirements to facilitate better learning delivery. This study tested variables latent profiles: construct and composite validity; Factorization Analysis (FA) with Principal Component Analysis (PCA); resulting in tolerable Kaiser-Meyer-Olkin (KMO) without modifications. The research questions (RQs) were formed from the top levels and cover 1.) the remedial treatment of cohort descriptives employing investigating whether the sample agrees or disagrees with the given sub-concepts formulated arguments; 2.) see the linear regressors amid variable pairs in the connection to whole modelizated effects. The 13-core characters related well with existing SSM4L2LPMQ framework model fit indices. Still, the sample size left saturation incomplete, indicating high RMSEA but somewhat excellent loadings, which support the resolution for the given respondent group.

keywords: Special Support, Motivation, Learning to Learn, L2L, Project Management, linear regression, factor analysis, structural equation.