Please use this identifier to cite or link to this item:
The Correlations among Faculty's Professional Background, Teaching Performance and Students' Learning Achievements in a University of Technology: A Hierarchical Linear Modeling Analysis
hierarchical linear modeling
faculty teaching performance
faculty' s professional background
students’ learning achievement
|Abstract:||科技大學校增多導致學生學能與表現差異愈來愈大，找出學生學習成就的關聯或影響因素成為當前科技大學校務研究的重點之一。本研究目的在探究科技大學教師專業背景、教師教學表現與學生學習成就之關聯。以個案科大234名教師及7,274名學生為對象，本研究利用此等對象在該校「校務行政系統」及「全國技專校院校務基本資料庫」中的資料，採用階層線性模式(hierarchical linear modeling, HLM)加以分析。結果顯示：(1) 激發學生學習動機，可以有效增進學生對教師教學表現的回饋；(2) 教師「年資」、「期刊論文」及「研討會論文」等三項專業背景，可正向預測教師教學表現；(3) 教師「年資」、「證照數量」、「研討會論文」及「業界經驗」等四項專業背景可調節學生自我評量與教師教學表現的關係；(4) 良好師生關係可正向預測教師教學表現與學生學習成就；(5) 透過期中評量的「質性」與「量化」對話，教師可引導學生達成課程目標，但課程內容太多及太難宜及時加以檢修；(6) 期中與期末評量在教師多元教學方法及評量方式認知呈現連貫一致，但學生倘不清楚「學習策略」可能產生疑慮。|
A huge increase in number of universities of technology (UT’s) leads to the diversification of students’ academic capabilities and performances. Thus, to explore the correlative or influencing factors of students' learning achievements has become one of the focuses of institutional research conducted by UT’s. The purpose of this study was to investigate the correlations among faculty's professional background, teaching performance and students' achievements in a UT. Totally, 234 faculty members and 7,274 students serving as its subjects, this study analyzed the data of the subjects in the case university’s “University Administration System” and nationwide “Base DataBase of Higher Technological and Vocational Education” by means of hierarchical linear modeling (HLM). Consequently, the following results are obtained: (1) Motivating and inspiring students leads to higher faculty’s teaching performance evaluated by students; (2) Faculty’s three professional backgrounds—seniority, journal articles and conference articles—can positively predict faculty’s teaching performance; (3) Faculty’s four professional backgrounds—seniority, certificates and licenses, conference articles, and working experiences in industries—can moderate the relationship between faculty’s students’ self evaluation and teaching performance; (4) Faculty-student relations can positively predict faculty’s teaching performance and students’ learning achievements； (5) Using the "qualitative" and "quantitative" dialogues in mid-term student’s evaluation of teaching (SET), faculty may guide their students reach the course goals , but the problem of too many and too difficult course contents should be timely examined and resolved; (6)It consistently reveals in mid-term and final SET’s that faculty use diverse teaching and assessments approaches, but students would doubt how to learn if they have no good learning strategies.
|Appears in Collections:||學位論文|
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.