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Integration into the discipline

Integration into the discipline

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Integration into the discipline

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  1. EFYE 2008 Conference, 7 - 9 May 2008, Wolverhampton, UK Integration into the discipline A focus group study on undergraduates’ first year experience at an Asian university Yang Min, Beverley Webster, Michael Prosser Centre for the Advancement of University Teaching The University of Hong Kong

  2. Structure • Research question and purpose • Literature: variation in first year experience; • Methods: focus group interviews; phenomenological and content analysis • Findings: variation in first year students’ academic integration across the disciplines

  3. Research question asked • To what extent are undergraduate students inducted into their academic discipline during their first year undergraduate education at the university under study?

  4. Purpose of the focus group study • Identify the variationin first year disciplinary learning in terms of six dimensions: (i) prior knowledge about the discipline (ii) induction to disciplinary knowledge (iii) induction to disciplinary research (iv) integration of learning from different courses in the discipline (v) induction to future progression in the discipline (vi) induction to disciplinary skills.

  5. Variation and diversity in FYE • Increased diversification in student population requires an in-depth understanding of the variation in first year experience (McInnis, James and McNaught, 1995; Kuh et al., 2006; Krause, Hartley, James and McInnis, 2005) • Benefits of studying variation • providing evidence of areas of difficulties in transition • developing strategies for facilitating academic and social integration (Krause, 2006; McInnis, 2001; Pitkethly and Prosser, 2001)

  6. Variation in learning approaches and learning outcomes • Students’ learning approaches and learning outcomes differ in the discipline and across the disciplines • Deep learners – focus on meaning and understanding, tend to achieve integrated/coherent knowledge or understanding of the discipline • Surface learners – focus on bits and pieces of knowledge or information, tend to fragmented/atomistic knowledge (Marton and Säljö, 1976a, 1976b;Prosser and Trigwell, 1999: 104-107; Ramsden, 2003: 53-61) • A clear relationship between students’ learning approaches and their perceptions of the learning environment within individual disciplines • teacher-centreddidactic teaching/assessment approaches tend to encourage the surface approach • student-centred facilitative teaching/assessment approaches tend to foster the deep approach (Prosser and Trigwell, 1999)

  7. Variation in learning and teaching styles in different disciplines • Variation in students’ learning styleacross disciplines • students from soft disciplines (English, history and psychology) scored higher on meaning orientation compared to those who majored in the hard disciplines (physics and engineering) (Entwistle and Tait, 1995: 96-98) • Variation in faculties’ teaching style across disciplines • soft disciplines (e.g., political science, sociology, psychology, history, English and economy) identified as affinity disciplines to improving teaching-learning, compared to the hard disciplines (Braxton, 1995; Gaff and Wilson, 1971)

  8. Variation in learning and teaching styles in different disciplines (Cont.) • Data from the National Survey of Student Engagement (NSSE) and Faculty Survey of Student Engagement (FSSE) in US: • seniors in the soft disciplines (e.g., social sciences, arts, humanities and education) and professional disciplines (e.g., nursing, architecture) score higher on deep learning scale and the subscales of higher-order learning, integrative learning and reflective learning • seniors in the hard disciplines (e.g., engineering & physical science) scored lower on most of these scales, whereas those in business and biological sciences clustered in the middle range • faculty members in the soft disciplines scored higher on emphasis on deep learning-associated approaches compared to faculty members in the hard disciplines (Nelson Laird, Shoup & Kuh, 2005; Nelson Laird, Schwarz, Kuh & Shoup, 2006)

  9. Methods • Data collection in Oct 2007 • 9 focus group interviews 40 undergraduate students (male = 21, female = 19) at the beginning of their2nd year • 9 soft & hard disciplines: arts, social sciences, architecture, business and economics, law, science, medicine, dentistry, engineering • Interview on induction into the academic discipline • 30-35 minutes in each focus group • Interview team • 1 interviewer +1 scriber +1 observer • Data analysis • phenomenographic analysis: relevant student responses were arranged into categories indicating more or less knowledge and/or understanding of the dimension under investigation • Content analysis: data associated with participants’ disciplinary skills/attributes arranged into parallel categories

  10. Results: prior knowledge about the discipline Q: What did you know about your major area(s) of study before entering university? • Slightly less than half of the participants were exposed to knowledge or information about their discipline • Prior knowledge limited to information about the degree programme • Just two participants held holistic view about the discipline b4 entering university • Others had little prior knowledge about what they would be learning in their undergraduate education

  11. Results: induction to disciplinary knowledge Q: ‘Could you give examples of key concepts, principles and theories that you have learned in your major area(s) of study? • Participants giving A and B category responses (i.e., more positive answers) were mainly from the soft disciplines • Less than half of the participants provided A or B category responsesby giving elaborated explanation of meaning and application of theories and concepts learned in their discipline • Participants providing the unsatisfactory responses were mostly from the hard disciplines

  12. Results: induction to disciplinary research Q: Could you give some examples of research areas and research methods in your major area(s) of study? • Less than one fourth of the participants gave A or B category responses relating to inquiry in the discipline • These participants were from social sciences and business and economics • the majority of participants in most disciplines had limited knowledge about disciplinary inquiry

  13. Results: integration of learning in the discipline Qa: How would your courses taken in the first and second years relate to each other? Qb: How would your courses taken in the first and second years relate to your major area of study? • 27 participants provided A or B category response in terms of course-to-course relationship (Qa) • disciplinary distribution for A and B category responses was even • Only 7 participants provided A or B category responses in terms of the relationship between what is learned in the courses with the discipline (Qb) • A and B category responses mainly contributed by those in the soft discipline

  14. Results: induction to future progression in the discipline: Qa: What type of employment, type of jobs, would you be able to get when you graduate? Qb: What postgraduate study opportunities might be available to you? • More than 3/4 of them giving A category responses associated with future employment and career (Qa) • Those in the professional disciplines typically anticipated entering discipline-related employment • Those in the pure/applied soft and pure hard disciplines expected finding more diverse job opportunities • Half of them giving A or B category responses relating to post-graduate study opportunities(Qb)

  15. Results: induction to disciplinary skills and attributes Q: What specific problem-solving, reasoning and reading/writing skills, would you develop? What kind of thinking skills and study skills do you need in your major discipline? • Problem-solving • emphasised more often by participants from the hard disciplines (science, medical and dental disciplines) • Critical thinking • stressed more often by participants from the soft and medical/dental disciplines • Professional skills/attributes • recognised more often by those from professional disciplines. • study-related skills • emphasised more often by the participants in the soft disciplines

  16. Conclusions • Variation at cross-disciplinary level did not occur in all the 6 dimensions of first year disciplinary learning • not much variation in the most and the least challenging dimensions – induction to disciplinary research; induction to future progression in the discipline • Where variation emerged, participants from soft disciplines provided A and B category responses more often than those from hard disciplines • e.g.,induction to disciplinary knowledge and integration of learning in the discipline • The first 4 dimensions were the most complex for the participants involved • esp.prior knowledge about the discipline and induction to disciplinary inquiry • Students in professional disciplines tended to differ from others in terms of perception of • disciplinary skills • future career progression

  17. Examples of categories - induction to disciplinary knowledge Table 2: The ways in which participants gave examples of theories/concepts in their discipline

  18. Examples of student responses - induction to disciplinary knowledge • A category • ‘The scope in which Politics is applied to could be large or small: from government-to-government to even individual-to-individual …Theories were covered in Year 2, e.g. rational theory, capitalism, democracy, etc. which helped student analyze the current situation in the world.’ (A student in social sciences) • Contract Law generally has to do with many aspects of life…It may not seem to have anything to do with us – how come would an ordinary person have to do with Law? However, that’s not true, if you just observe things around us. You’d find that Law is closely related to us.’ (A student in Law) • C category • ‘[What we learned in Year 1 of Biotechnology] was basically the revision of what we learned in A-level courses, with more explanations. [For instance,] how the cell-to-cell communication is like; and the deeper things such as signals...’ (A student in science)

  19. Examples of categories - integration of learning in the discipline Table 5: Participants’ perceptions of the course-major relationship

  20. Examples of student responses –integration of learning in the discipline • A category • ‘The courses we have taken are related to my major [Biotechnology] because all courses are about genetics and reproduction.’ [A Student in Science] • B category • ‘I think all courses taken have been designed to relate to Business (her major). You may not agree with all the concepts learned, but surely they are related to Business.’ (A Student in Business and Economics) • C category • ‘Yes, the courses are related to my majors. Mathematics (his first major) has many branches such as Statistics. You have to take three to four courses to learn each branch. Risk Management (his second major) covers all course materials that we need to learn in order to take the examination for applying for the license [in Risk Management]’ (A student in Science)

  21. Thank you