Tentative course calendar/schedule:
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In class |
Before class |
After class |
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assessment (score)
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Time investment (hour) |
Week |
Date |
co-instructor, except meishiu |
content |
detailed Contents |
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essay writing |
oral presentation |
class Q&A; share |
in class |
outside class |
1 |
218(initial withdrawal by 224) |
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Introduction |
databases; data analysis skills and packages |
syllabus,Q&A,self-introduction
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explore |
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3 |
3 |
4.5 |
2 |
225 |
Lecturer Toshiyuki Hasumi |
literature databases |
Literature
1. Basic research: database => WoS, Scopus
search query, record keeping
2. Bibliometric => purpose: to learn about the field (phd/masters students)
3. VOSviewer => usage -> cocitation/bib coup/coword |
lecture, discussion, hands-on etc. |
explore |
explore, essay |
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3 |
3 |
4.5 |
3 |
304 |
same as above |
literature data analysis |
1. hands-on: run VOSviewer
2. explain results from VOSviewer
3. Results: how to write |
same above |
same above |
same above |
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3 |
3 |
4.5 |
4 |
311 |
3hr class; 6hr advisory
311-313 Prof. Henrik Saalbach, University of Leipzig |
multilanguage/culture/development research |
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same above |
same above |
same above |
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3 |
3 |
4.5 |
5 |
318 (deduct) |
Prof. Saalbach 3hr advisory |
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3 |
3 |
4.5 |
6 |
325 |
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basic multivariate analysis |
Fischbach2013OutcomeSesLuxembourg_pisa06_basicStatistics_LID |
one student brief the paper, discussion, and hands-on |
write essays; read the paper; one student prepars briefs |
review; write essays |
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10 |
3 |
3 |
4.5 |
7 |
401 |
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CFA |
Marsh2013validityMathSciAffect ArabAnglo_timss07_cfa_JEP |
same as above |
same as above |
same above |
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* |
3 |
3 |
4.5 |
8 |
408 |
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SEM |
Chiu2020ExploringModelsForIncreasing_pisa12_mediate SEM_ETRD |
same as above |
same as above |
same above |
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* |
3 |
3 |
4.5 |
9 |
415 |
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multilevel analysis |
Chiu2012_IE_BFLPE_combine_timss03_hlm_JEP |
same as above |
same as above |
same above |
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* |
3 |
3 |
4.5 |
10 |
422 (final withdrawal) |
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machine learning |
Wang2023timss2019EastAsiaMathAch_randomForest_IJSME |
same as above |
same as above |
same above |
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* |
3 |
3 |
4.5 |
11 |
429 |
3hr class; 6hr advisory
423-502 Prof. Maurizio Toscano, Univeristy of Melbourne |
research/analysis beyond empirical databases |
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lecture, discussion, hands-on etc. |
same as above |
same above |
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* |
3 |
3 |
4.5 |
12 |
506 (deduct) |
Prof. Saalbach 3hr advisory |
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14 |
513 |
Lecturer Hasumi |
GAI-infused data analysis |
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same as above |
same as above |
analysis, essay |
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3 |
3 |
4.5 |
13 |
520 (deduct) |
Prof. Toscano 3hr advisory |
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15 |
527 (deduct) |
Prof. Toscano 3hr advisory |
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3 |
3 |
4.5 |
16 |
603 |
Lecturer Hasumi |
present final essay |
Demo: how to present
students hands-on: revise ppt and present |
demo, hands-on, student present, discussion |
prepare presentation |
analysis, essay |
18 |
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3 |
3 |
4.5 |
17 |
610 (flexible) |
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final written essay |
30 |
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18 |
617 (flexible) |
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Total score |
100 |
48 |
10 |
42 |
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Assessment: essay, oral presentation, essay and weekly journal (view the assessment table for details).
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1. For the paper-reading weeks, please ask at least one question for the assigned paper before class. We will discuss at least one of each student's questions first and go for the other questions if we have time.
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2. GAI use regulation: Thorp, H. H. (2023). ChatGPT is fun, but not an author. Science, 379(6630), 313-313.
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3. Essay rubric: (http://wid.ndia.org/about/Documents/WID_EssayRubric.pdf);oral presentation rubric (https://www.science.purdue.edu/Current_Students/curriculum_and_degree_requirements/oral_rubrics_gray.pdf)
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Chiu, M.-S. (2020). Exploring models for increasing the effects of school information and communication technology use on learning outcomes through outside-school use and socioeconomic status mediation: The Ecological Techno-Process. Educational Technology Research and Development, 68, 413–436.
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Chiu, M.-S. (2012). The internal/external frame of reference model, big-fish-little-pond effect, and combined model for mathematics and science. Journal of Educational Psychology, 104, 87-107.
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Chiu, M.-S. (2023). Gender differences in mathematical achievement development: A family psychobiosocial model. European Journal of Psychology of Education. https://doi.org/10.1007/s10212-022-00674-1
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Fischbach, A., Keller, U., Preckel, F., & Brunner, M. (2013). PISA proficiency scores predict educational outcomes. Learning and Individual Differences, 24, 63-72.
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Marsh, H. W., Abduljabbar, A. S., Abu-Hilal, M. M., Morin, A. J., Abdelfattah, F., Leung, K. C., Xu, M. K., & Nagengast, P. (2013). Factorial, convergent, and discriminant validity of TIMSS math and science motivation measures: A comparison of Arab and Anglo-Saxon countries. Journal of Educational Psychology, 105, 108-128.
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Wang, F., King, R. B., & Leung, S. O. (2023). Why do East Asian students do so well in mathematics? A machine learning study. International Journal of Science and Mathematics Education, 21(3), 691-711.
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related papers and resources.
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