How Highly Achieved Students Differ from the Others? A Text-mining Approach to Personal Learning Goals (69813)
Session Chair: Susan Lohret
Sunday, 23 April 2023 09:30
Session: Session 1
Room: Falls Church
Presentation Type:Oral Presentation
People often set goals at the start of a new event in their life. Goals are related to performance across different domains, including sports, psychotherapy, leadership, health care, as well as education. Those students who set learning goals are found to have higher learning motivation, more persistence in learning, better course attendance, and better academic performance than their counterparts. Previous studies showed students benefited most from setting specific, challenging, measurable, and achievable learning goals than their counterparts did. While goal-setting activity appears to be an effective and inexpensive way to enhance learning performance, how learning goals vary as a function of students’ course grades remains under-explored. Rather than classifying students’ learning goals into pre-established categories for summative investigation, this research adopts a text-mining approach to examine the underlying similarities and differences directly. We have invited 192 university students to set three different learning goals at the beginning of a semester. Results from 552 valid responses indicated that highly achieved students differ from their counterparts in terms of the clarity of expression, the usage, and the characteristics of words used in setting their personal goals. In general, these students expressed themselves with more clarity, more purpose-driven, and more variety of words, which provides an opportunity for us to learn from the highly achieved students. Other theoretical advances and practical advances in education, teaching and learning will also be discussed.
Authors:
Hilary K. Y. Ng, Hong Kong Metropolitan University, Hong Kong
Lester C. H. Chan, Hong Kong University of Science and Technology, Hong Kong
About the Presenter(s)
Dr Hilary Ng is a University Assistant Professor/Lecturer at Hong Kong Metropolitan University in Hong Kong
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