1 Preparing Students for Successful Transition in the New Academic Structure C. S. Tong Hong Kong Baptist University.

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Presentation transcript:

1 Preparing Students for Successful Transition in the New Academic Structure C. S. Tong Hong Kong Baptist University

Some World Trends The world is undergoing fundamental economic, technological, social and cultural changes: Knowledge based economy: emerging industries founded on knowledge, technology and innovation Lean management structures, streamlined networks and flexible staffing  Life-long learning  Mobility  Globalization 2

The New Secondary Curriculum Education Commission Sept 2000: the overall aims of education in Hong Kong for the 21st Century -- To enable every person to attain all-round development in the domains of ethics, intellect, physique, social skills and aesthetics according to his/her own attributes so that he/she is capable of life-long learning, critical and exploratory thinking, innovating and adapting to change; filled with self-confidence and a team spirit; willing to put forward continuing effort for the prosperity, progress, freedom and democracy of their society, and contribute to the future well-being of the nation and the world at large. 3

Principles of Reform Student-focused “No-loser” Quality Life-wide learning Society-wide mobilisation 4

Focuses of Reform Reforming the admission systems and public examinations so as to break down barriers and create room for all Reforming the curricula and improving teaching methods Improving the assessment mechanism to supplement learning and teaching … 5

Recommendation for University Universities should reform their first degree programmes so as to strike a right balance between the breadth and the depth of such programmes. Universities should avoid excessive reliance on the results of public examinations and should give due consideration to the overall performance of students in order to encourage all-round development in schools. 6

Liberal Studies/General Education Importance of LS in the HKDSE and GE at universities in the face of the world trends in the workplace Broad-based admission (eg Admission by Faculty) at universities  More difficult to differentiate and select the right students for the programmes  Need to adopt new teaching pedagogies and assessments (OBTL) 7

OLE/SLP Less emphasis on HKDSE scores Universities to pick students with the potential and profile that befits its role and mission  Each university to be judged by its success in training students with its declared graduate attributes Potential problem  Double cohort in 2012 and big increase in applicant pool size School-University-Government collaboration 8

9 Simulation Study on Admission Summary of the Improvement made by Steps Ranking the Students by 4 Steps Selection of the Important Independent Variables Confirmation of Dependent Variable Used Grouping of Independent Variables

10 Division of Independent Variables Group 1Group 2Group 3Group 4 CdcMax20Score; CdcChiScore; CdcEngScore; CdcMax30Score. School Reference Report Ability Score (13 variables) Self Recommendation Scheme Score Applicant’s Choice of the Program

11 Dependent Variable GpaCum.2 GpaCum.2 describes the second term cumulative GPA, which is the first year cumulative GPA. Feasible Range: [0,4] Based on different coefficients, the combination of independent variables can describe [-∞, +∞]. The inconsistence of the dependent variable and independent variables may result in an unexpected result. This conclusion can be get from the following table.

12 R2R2.157** Adjusted R 2.153** N 2825  Note: R 2 : an estimate of the proportion of variance accounted for by regression Adjusted R 2 : a better estimate of the population value of R 2 N: total number of all the students from 2006 to 2008  The result is based on all the student from 2006 to  Here, backward regression is used to analyze the relationship between the independent variables and dependent variables. The option tells how significant it must be to avoid removal in backwards selection. At each step, the variable with the largest probability-of-F value is removed, provided that the value is larger than POUT(the default value is 0.10).

13 Group the Selected Variables 1 Entrance Examination Score CdcMax20Score, CdcChiScore, CdcEngScore 2 Applicant’s Choice of the Program Offer Priority 3 Other Ability Score Considered Industriousness, Responsibility, Communicate, Overall, etc

14 4 Steps in Ranking Performance Indicator Ability Score Offer Priority CdcMax20Score, CdcEngScore, CdcChiScore Step 4 Step 3 Step 2 Step 1  Note: Offer Priority has two sets. Set 1: Priority 25. Set 2: Banding 5

15 2 Models for handling language scores in Step 1 Step 1-a CdcMax20 Step 1-b CdcEngScore Step 1-c CdcChiScore Step 1-a CdcMax20 Step 1-b Max (Eng, Chi) Step 1-c Sum (Eng, Chi) Step 1

16 1 st Model  For each faculty, the following is the percentage of applicants that can be distinguished with respect to each step (for 2006~2008).  Faculty of Arts  Note: Step 1= Step 1- c

17 Conclusions Academic Scores unlikely to be sufficient for ranking students for admission  HKCEE not available in 2012  Expect 2-3 times more applicants  More levels for HKDSE42 vs CDC30 Non-Academic Abilities useful but still not sufficient in ranking students for admission Need to make use of OLE/SLP/Interview

Conclusions Statistical research find little correlation between entrance academic scores with university performance  Increasingly looking at non-academic achievements as more reliable predictor  Team work, communication skills, happy learning environment may produce win-win situations 18

Sharing of Experience How to achieve success in an interview: Passion Genuine Aware of Current Events Good Communication Skills/EQ …all attributes honed in OLE/SBA etc 19

Conclusions Overall, students may have less diversified background knowledge (only two or three electives) Schools should treat OLE as broadening for its own sake, as opposed to gaining bonus marks for university admission Schools to enhance career/further studies counselling with a view to finding the best match for the student (not based on perceived pecking order) 20

21 Thank you!