Curriculum Vitae Zhidong Zhang, Ph. D. COLLEGE OF EDUCATION

Curriculum Vitae Zhidong Zhang, Ph. D.
THE DEPARTMENT OF TEACHING, LEARNING AND INNOVATION
COLLEGE OF EDUCATION
THE UNIVERSITY OF TEXAS AT BROWNSVILLE
Zhidong Zhang, Ph. D.
Assistant Professor
Department of Teaching, Learning and Innovation
The College of Education
2.304 Education and Business Complex
One West University Blvd.
Brownsville, Texas 78520
Tel :(956) 882-5723
Email: [email protected]
Education
Postdoc McGill University, Canada, Quantitative Psychology in the Department of Psychology May 2008.
Research direction: multi-level/hierarchical linear modeling, statistical computing, Bayesian network,
multidimensional scaling, machine learning, biostatistics and bioinformatics.
Ph. D. McGill University, Canada, Quantitative Methods, Psychometrics and Statistics Methods in Applied
Cognitive Science, in the Department of Educational Psychology, May 2007.
Research direction: cognitive process analysis and assessment with quantitative methods.
M. A. The University of Illinois at Chicago, College of Medicine, Educational Measurement in Medical
Education, July 1992.
Research direction: evaluating and modeling cognitive and learning processes in medical schools;
medical informatics and biostatistics
B.A.
Harbin Medical University, P. R. China, Public Health and Quantitative Methods, July 1986.
Research interests and direction: biostatistics, epidemiology, and quantitative methods.
Publications
Zhang, Z., & Duarte, G. (2014). Experimental methods and data collection. In C. I. O. Okeke &
M. M. V. Wyk (Eds.), The fundamentals of planning, designing, conducting and reporting
research findings. Oxford, UK: Oxford University Press (Manuscript has been accepted).
Zhang, Z, & Bussert-Webb. K. (2014). Reading and language beliefs: A hierarchical linear model.
Manuscript in preparation.
Bussert-Webb. K. & Zhang, Z., (2014). Reading attitudes of Texas school students. Manuscript in
Preparation.
Telese. J., & Zhang, Z. (2014). Elementary teachers’ pedagogical content knowledge for teaching
mathematics, self-efficacy, and student achievement: A path analysis. Manuscript
in preparation.
Zhang, Z., Zhang, Z-C., & Jiang, H. (2014). Multilevel analysis of Children’s cognitive and
behavioral problems of migrant population. Manuscript in preparation.
Zhang, Z. & Lu, J. (2014). Quantitative assessment of medical student learning through effective
cognitive Bayesian representation. Manuscript in preparation.
Zhang, Z., Zhang, Z-C., & Wen, D. (2014). Reliability Issues of CBCL and YSR in children’s
behavioral assessment. Manuscript in preparation.
Lu. J., & Zhang, Z. (2013). Scaffolding argumentation in intact class: Integrating technology
and pedagogy. Computers & Education, 69 (11), 189-198.
Lu, J., & Zhang, Z. (2013). Assessing and supporting argumentation with online rubrics.
International Education Studies, (6) 7, 66-77.
Wang, X., Zhang, Z., Zhang, X, & Hou, D. (2013). Validation of the Chinese version of the
epistemic beliefs inventory using confirmatory factor analysis. International Education
Studies, (6)8, 98-111.
Lu, J. & Zhang, Z. (2012). Understanding the effectiveness of online peer assessment: A path
model. Journal of Educational Computing Research, 46 (3), 317-337.
Zhang, Z & Telese, J. (2012). Determining a model to predict Hispanic pre-service teachers’
success on the Texas examination of education standards. Teach Education and Practice,
25 (3), 388-401.
Zhang, Z, & Takane, Y. (2010). Statistics: Multidimensional scaling. In E. Baker, B. McGaw & P.
Peterson (Eds.), International Encyclopedia of Education (3rd Edition). Oxford, UK: Elsevier.
Zhang, Z. (2010). Custom education—introduction to research methods. New York, NY: Pearson
Learning Solutions.
Takane, Y., & Zhang, Z. (2009). Algorithms for DEDICOM: Accelerate, decelerate, or neither?
Journal of Chemometrics, 23(7-8), 364-370.
Leung, K. H., & Zhang, Z. (2008). How cybercoaching system works: An example with statistics.
In T. Kidd & H. Song (Eds.), Handbook of research on instructional systems and Technology
(pp. 343-359). NY: Information Science Reference.
Zhang, Z. & Leung, K. H. (2007). Design of Diagnostic Cognitive Assessment for Web-Based
Learning Environments with Bayesian Network Models. In T. Bastiaens & S. Carliner (Eds.),
proceedings of E-learn 2007: World conference on E-learning in corporate, government,
healthcare, & higher education (6701-6706), Quebec, QC, Canada.
Leung, K. H., & Zhang, Z, (2005). Cybercoaching System. In G. Richards (Ed.), Proceedings of
E-learn 2005: World conference on E-learning in corporate, government, healthcare, & higher
education (366-368), Vancouver, BC, Canada.
Scholarly Presentations
Zhang, Z. Supervised Learning Bayesian Network Model as an Assessment Tool in Learning Sciences.
Paper will be presented at the Conference of Academic and Business Research Institute, Mar. 27-29,
2014. San Antonio, TX.
Zhang, Z, & Zhang, Z-C. Children’s Mental Health and Behavioral Problems of Migrant Population
Paper will be presented at the Conference of Chinese American Educational Research and
Development Association (CAERDA), April 3-7, 2014, Philadelphia, Pennsylvania.
Zhang, Z., Zhang, Z-C., & Wen, D. (2014). Reliability Issues of CBCL and YSR in children’s
behavioral assessment. Paper will be presented at Education and STEM Conference, June
14-18, 2014.
Telese, J., & Zhang, Z. Elementary Teachers’ Pedagogical Content Knowledge for Teaching
Mathematics, Self-efficacy, and Student Achievement: A Path Analysis. Paper presented
at 37th SERA annual meeting, Feb. 10-13, 2014, New Orleans, LA.
Zhang, Z., & Bussert-Webb, K. The reading dispositions, practices and access of 2568 Texas high
school students. Paper presented at 15th Annual Research Symposium, UT-Brownsville,
April 5, 2013.
Hsuing, W., Lu, P., Zhang, Z., Ledingham, C., O’Connor, B., & Shin, Y. Faculty collaboration:
Stories from UTB faculty learning community. Paper presented at 15th Annual Research
Symposium, UT-Brownsville, April 5, 2013.
Telese, J., & Zhang, Z. Examining the level of academic rigor in a school district. Paper presented
at the SERA 36th annual meeting, February 6-9, 2013, San Antonio, Texas.
Zhang, Z., & Lu, J. Argumentative assessment with Bayesian network models in current debatable
social issues. Paper is presented at the Conference of Chinese American Educational Research
and Development Association (CAERDA), April 13-17, 2012, Vancouver, BC. Canada.
Lu, J., & Zhang, Z. Assessing arguments: Supporting argumentation with online rubric-based
assessment. Paper is presented at the AERA annual meeting, April 13-17, 2012, Vancouver, BC,
Canada.
Zhang, Z. Diagnostic assessment model based on cognitive feature trajectories in a clinical learning
environment with Bayesian network. Paper presented at the 14th Annual Research Symposium
at the UT-Brownsville. April, 2012, Brownsville, TX.
Zhang, Z. Quantitative assessment of medical student learning in solving a deteriorating patient
problem through effective cognitive Bayesian representation. Paper presented at 18th
International Conference on Learning, July 5-8, 2011, Mauritius.
Lu. J., & Zhang, Z. Facilitating informal argumentation skills through online rubric-based assessment.
Paper presented at the Conference of Chinese American Educational Research and Development
Association (CAERDA), April 7-10, 2011, New Orleans, LA.
Zhang, Z. Quantitative Structural Representations of Cognitive Tasks for Both Learning and
Assessment in Complex Cognitive Environments Paper presented at the AERA annual meeting,
April 7-9, 2011, New Orleans, LA.
Zhang, Z. Developing and modeling cognitive tasks for dynamically diagnostic assessment: A
Bayesian network representation. Presented at 17th International Conference on Learning, July
5-9, 2010, Hong Kong, HK.
Zhang, Z. Modeling cognitive feature trajectories in a clinical learning environment with Bayesian
Network. Presented at the Conference of Chinese America Educational Research and
Development Association (CAERDA), April 29-30, 2010, Denver, CO.
Takane, Y., & Zhang, Z. Algorithms for DEDICOM: acceleration, deceleration, or neither? Paper
presented at the 74th Annual Meeting of the Psychometric Society, London, UK, June, 2009.
Zhang, Z., Takane, Y., & Lu, J. Modeling situation interpretations and cognitive trajectories in a
clinical problem solving process with Bayesian network. Paper presented at the 73rd Annual
Meeting of the Psychometric Society, Durham, NH, USA, July, 2008.
Lu, J., Law, N., Chan, C., & Zhang, Z. (2008, June). Understanding students’ argumentation
processes with data mining tools in a collaborative knowledge building environment. Paper
presented at the international conference on Educational Data Mining, Montreal, Quebec,
Canada.
Zhang, Z., Lu, J., & Wiseman, J. (2008, May). Understanding and assessing students’ clinical
reasoning in the context of simulated emergency medical case. Paper presented at the annual
meeting of the Association of Faculties of Medicine of Canada, Montreal, QC, Canada.
Zhang, Z., & Frederiksen, C. (2007, April). Diagnostic cognitive assessment in complex
domains of learning and performance: A Bayesian belief network approach. Presentation at the
AERA annual meeting, Chicago, IL, USA.
Frederiksen, C., Mercier J., Donin, J., Bracewell, R., Zhang, Z., & Chung, T. (2003, May). A webbased computer coach for problem-based learning. Centre for the Study of Learning and
Performance Research and Technology, Montreal, Canada.
Frederiksen, C., Donin, J., Bracewell, R., Mercier, J., & Zhang, Z. (2002, April). Human Tutoring
and the Design of Computer Coaching Systems. Paper presented at the 83rd Annual Meeting of
the America Educational Research Association, New Orleans, LA, USA.
University meetings and seminars
Zhang, Z. Overview of repeated measure analysis. A presentation at Quantitative Psychology
Lab meeting, Department of Psychology, McGill University, Montreal, QC, Canada,
April, 2009
Zhang, Z. Introduction to statistical analysis of macro-comparative data. A presentation
at Quantitative Psychology Lab meeting, Department of Psychology, McGill University,
Montreal, QC, Canada, March, 2009
Zhang, Z. Multidimensional scaling and color reference: A psychological dimension explanation.
A presentation at Quantitative Psychology Lab meeting, Department of Psychology, McGill
University, Montreal, QC, Canada, Jan., 2009
Zhang, Z. Bayesian networks as diagnostic assessment tools in cognitive processes. A
Presentation at Quantitative Psychology Lab meeting, Department of Psychology, McGill
University, Montreal, QC, Canada, Feb., 2009
Zhang, Z. Modeling diagnostic cognitive assessment for knowledge and problem solving skills in
statistics learning. A presentation at Quantitative Psychology Lab meeting, Department of
Psychology, McGill University, Montreal, QC, Canada, May, 2008
Zhang, Z. Application of a Bayesian belief network to diagnostic cognitive assessment in studies
In statistics learning and performance. A presentation at seminar, Faculty of Education,
McGill University, Montreal, QC, Canada, Jan. 2007.
Zhang, Z. Bayesian networks and graphical models in diagnostic assessment. A presentation at
Cognitive Model Seminar, Faculty of Education, McGill University, Montreal, QC, Canada,
Sept. 2006.
Zhang, Z. Evaluation variables and statistical model in diagnostic assessment. A presentation at a
small group discussion, Faculty of Education, McGill University, Montreal, QC, Canada, March
2005.
Zhang, Z. Measurable objects and evidence variables in performance-based assessment. A
presentation at Cognitive Assessment seminar, Faculty of Education, McGill University,
Montreal, QC, Canada, Mar. 2005.
Zhang, Z. Inference in Bayesian networks and psychometric model. A presentation at Cognitive
Methods Seminar, Faculty of Education, McGill University, Montreal, QC, Canada, Oct.
2005.
Zhang, Z. Item Response Theory and performance-based assessment. A presentation at
Seminar 668 (Cognitive Assessment), Faculty of Education, McGill University, Montreal, QC,
Canada, Jan. 2004
Zhang, Z. Modern test theories, models and cognitive diagnostic assessment. A presentation at
Seminar 668, Faculty of Education, McGill University, Montreal, QC, Canada, Nov. 2004.
Zhang, Z. Propagation in graphical belief models presented at Seminar cognitive research
methods, Faculty of Education, McGill University, Montreal, QC, Canada,
June 2004.
Research Grants
Grants being planned
June 2014
Title: Elderly people’s cognitive and behavioral problems in Northeast China.
Investigation position: Principal investigator
Amount: $450,000
Duration: 4 years
Award information: N/A
We plan to develop a research proposal on older people’s cognitive, psychological and behavioral issues of
Northeast China in Oct. 2014. ASEBA empirical assessment tools will be used in this research studies.
Hierarchical Linear Models (HLM) will be used to analyze the data.
ASEBA rationale: The Older Adult forms (OABCL and OASR) can greatly improve assessment of older
adults in a variety of contexts, including psychiatric and psychological evaluations; medical care;
assessments following significant life changes, such as loss of a loved one or a move to an assisted living
environment; and evaluations before and after planned changes and interventions. The OASR obtains older
adults’ self-reports of diverse aspects of adaptive functioning and problems. The OABCL is a parallel form
for obtaining reports from people who know the adult well.
Cross-informant comparisons make it easy to see similarities and differences between self-reports and
reports by other people.
May 2014
Title: Parent Perceptions of School-based Behavior Intervention Plans
Investigation position: Co-principal investigator
Amount: $300,000
Duration: 3 years
Award information: N/A
The level of inappropriate behaviors in schools (e.g., non-compliance to teacher directives to basic bullying
to shootings) is escalating in our society. School personnel often implement a Behavior Intervention or
Management Plans (BIP) to try to alleviate the inappropriate behaviors before they become violent. This
study will examine the efficacy of the use of BIPs in public schools. The purposes of the study are (a) to
quantitatively measure the efficacy of BIPs by tracking in school misbehaviors by frequency and
topography, and (b) to qualitatively examine the perceptions of the participants (i.e., children, teachers, and
parents).
The research proposal will be submitted to National Science Foundation (NSF) in Dec., 2014 or June,
2015.
Grants submitted
Sept. 2013
Title: Transforming Education through Neuroscience and Undergraduate Research (TEN)
Investigation position: Co-principal investigator
Amount: $700,000
Duration: 4 years
Award information: N/A
The research proposal has be submitted to IES in Dec. 2013
Grants funded
June 2013
Title: Children’s Mental Health, Cognitive and Behavioral Problems of Migrant Population in Northeast
China
Investigation position: Principal investigator
Amount: $250,000
Duration: 4 years (from June 2013-June 2017)
Funding information: Funded
Jan. 2011
Title: Understanding students’ argumentation skills during inquiry learning.
Investigation position: Co- principal investigator.
Amount: HK$ 111,105.
Duration: Jan. 5, 2011 to Feb. 28, 2012
Funding information: Funded
Academic Awards and Research Supports
2008
SSHRC grants of the Department of Psychology
McGill University, Montreal, QC, Canada
2004
Faculty of Education and Research Fellowships
McGill University, Montreal, QC, Canada
2002
Faculty of Graduate Studies and Research Fellowships
McGill University, Montreal, QC, Canada
2001
McGill Major Fellowship
McGill University, Montreal, QC, Canada
2000
McConnell Fellowship
McGill University, Montreal, QC, Canada
1999
McGill Statistics Tutor Project Grant
McGill University, Montreal, QC, Canada
Psychometric and Statistical Analysis Tools and Techniques
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SAS and SPSS: intermediate univariate, and multivariate analysis.
Amos and Mplus: path analysis and structural equation modeling, analysis
HLM: multilevel analysis/ hierarchical linear model and longitudinal data analysis
Matlab: application to linear algebra (matrix evaluation) related to multivariate analysis.
R: application to multivariate analysis
Bayesian network analysis technique: employed to hierarchical data analysis (BayesiaLab, 2014).
IRTPro (2013): applied to item analysis and analytical report.
Research Experience
As a research project developer, consultant and data analyst
Aug. 2013
Data analyst
Reading and language belief data
College of Education, UT at Brownsville
Sept. 2012
Data analyst
Using hierarchical linear model to explore elementary reading and math performances
and relevant factors in south Texas area
College of Education, UT at Brownsville
Aug. 2011
Data analyst
Scaffolding argumentation during reading and evaluation with support of CSCL tools
Faculty of Education, Hong Kong University, Hong Kong
Jan. 2011
Research project developer and data analyst
Understanding students’ argumentation skills during inquiry learning.
Faculty of Education, Hong Kong University, Hong Kong
Jan. 2008
Research Project Consultant
Development of an Instrument to Measure a Learning Process of Clinical Medical Students and
Residences
CHSLD (Centre d'hébergement de soins de longue durée) Jewish Eldercare at McGill University,
Montreal, QC, Canada
April 2008
Research Project Consultant
Validation of an Instrument to Assess Clinical Residence Learning in Alternative Settings
The Centre for Medical Education at McGill University, Montreal, QC, Canada
As research assistant
2005-2007
Research assistant
Robust analysis of psychometric models of cognitive diagnostic assessment, model fit and validity
Faculty of Education, McGill University, Montreal, QC, Canada
2002-2005
Research assistant
Exploration and test of psychometric models of cognitive diagnostic assessment in a web-based
learning system
Faculty of Education, McGill University, Montreal, QC, Canada
2000-2002
Research assistant
Design of Psychometric models of cognitive diagnostic assessment for a web-based learning system
in statistics learning domain
Faculty of Education, McGill University, Montreal, QC, Canada
1998-2000
Research assistant
Development of a web-based, computer-coached learning system
Faculty of Education, McGill University, Montreal, QC, Canada
Instructional Experience
Aug. 2009-2014 Assistant Professor, College of Education, at the UT Brownsville.
Courses taught
EDCI 6300: Foundations of Research Methods (Master’s level)
The course is an introduction to research methodology in education. It focuses on the relationship between
research problem, questions and design and introduces students to techniques for collecting and analyzing
research data. The course emphasis is on writing an analysis and synthesis of research methodology and
findings in empirical articles.
EDCI 6302: Practitioner Research Methods (Master’s level)
This course is an introduction to field-based research methodology with an emphasis on the teacher as a
researcher and on reflective teaching and teaching as decision-making. This is a field-based course.
EDCI 6367: Statistical Methods (Master’s and doctoral levels)
This course provides masters’ and doctoral students with intermediate statistical knowledge and problem
solving skills with statistics analytical software such SPSS. Students can bring their own statistical
problems or use problem examples in the textbook. Basic statistics topics are included such as t-test, oneway ANOVA, and two-way ANOVA.
EDFR 8301: Qualitative Research Methods (Doctoral level)
The course is an introduction to qualitative research methods in social sciences, especially in educational
fields. It focuses on the understanding of practical approaches to qualitative research. Students will learn
necessary concepts and methods in qualitative research such as research problem, questions and design, and
build techniques for collecting and analyzing research data. The course will also emphasize writing, data
collection and analysis, and presentation of research findings.
EDFR 8302: Quantitative Research Methods (Doctoral level)
This course includes following topics: foundations of quantitative research, development of instruments,
inferential statistics, experimental design, quasi-experimental design, non-experimental design, one-way
and two-way ANOVA, non-parametric tests, correlation and regression, multiple regression, multilevel
modeling, structural equation modeling
DFR 8303: Statistical Analysis in Educational Research: From Bivariate to Multivariate Analysis
(Doctoral level)
This course establishes a bridge between intermediate and multivariate analysis. The doctoral students who have
less statistical knowledge and skills can start from this course towards their advanced data analysis.
The topics include but are not limited to: one-way between subjects analysis of variance, bivariate
Pearson correlation, multiple regression with two predictor variables, factorial analysis of variance,
analysis of repeated measures, and binary logistic regression.
EDFR 8305: Multivariate Analysis (Doctoral level)
This course provides advanced multivariate data analysis in both theory and analytical techniques. Students
will choose one of data analysis software such as SPSS, SAS and R to complete their data analyses.
Students can bring their own data or use textbook data to simulate their thesis data analysis. This course
covers a broad spectrum of multivariate analysis topics such as multivariate analysis of variance
(MANOVA), principal component analysis, hierarchical linear models, path analysis and structural
equation modeling.
Course prepared
EDCI 7336: Measurement and Assessment in Education (Master’s and Doctoral level)
The content of this course will include basic statistical concepts and descriptive statistics for educational
measurement, correlation and prediction, normal distribution and the meaning of test scores, reliability and
validity of measurement, item analysis and classroom test development, development and use of selectedresponse items, assessment of behavior and constructs, performance and behavioral assessments and
portfolios, classroom assessment and standardized achievement tests, the use of aptitude tests in the
schools, scores, traits and knowledge representations in assessments, item response theory and factor
analysis, and alternative assessment and cognitive diagnostic assessment
EDFR 8304: Ethnographical Research Methods (Doctoral level)
This course includes ethnographical epistemology, theories and methods. The course further focuses on
participant observation, writing field notes and interviewing. Data collection, techniques of analysis, and
ethical issues are also foci of the course.
EDFR 8307: Program Evaluation in Education (Doctoral level)
This course provides an introduction to the design and implementation of evaluations of educational
programs. Students will be introduced to the theory and practice of educational evaluation by reviewing
evaluation reports and papers, preparing evaluation designs, and developing evaluation instruments. Topics
focus on all aspects of the design and implementation of educational evaluations, including considering the
audience and purposes for evaluations, developing an evaluation plan, preparing the evaluation design,
designing evaluation instruments and measures, collecting, analyzing, and reporting evaluation data, and
adhering to professional ethical principles.
EDFR 8308: Categorical Data Analysis (Doctoral level)
Categorical data are very rich data resources in social sciences and medical sciences. This course provides
categorical data analytical methods and techniques. The topics mainly focus on the generalized linear
model, log-linear model, logistic regression with continuous predictors, logistic regression with categorical
predictors, and logistic regression for multi-category outcomes.
EDFR 83**: Multilevel analysis/ modeling (Doctoral level)
Multilevel modeling and hierarchical linear models (HLM) are variant terms for where are broadly called
linear mixed models (LMM) which also contains the techniques of longitudinal data analysis. The course
designs are referred to Multilevel Analysis, an Introduction to Basic and Advanced Multilevel Modeling,
authored by Dr. T. A. B. Snijders, and Dr. R. J. Bosker and Hierarchical Linear Modeling-Guide and
Applications edited by Dr. G. D. Garson.
2000-2008 Lecturer and Teaching Assistant, The Faculty of Education, McGill University, Quebec, Canada
Jan. 2008
Lecturer, McGill University, Montreal, QC, Canada
EDPE 684: Advanced Multivariate Analysis (Doctoral level)
Multivariate repeated measures with between and within factors, principle component analysis,
discriminant analysis and classification, canonical correlation analysis, unrestricted factor
analysis, confirmatory factor analysis, path analysis, structural equation modeling (SEM)
and log linear model
Jan. 2007
Lecturer, McGill University, Montreal, QC, Canada
EDPE682: Univariate/Multivariate Analysis (Doctoral level)
Multiple regression (REG), univariate general linear model for analysis of variance and regression
(GLM), multivariate analysis of variance (MANOVA), multivariate general linear model (GLM),
univariate analysis of covariance (ANCOVA), and multivariate analysis of covariance
(MANCOVA)
Jan. 2007
Lecturer, McGill University, Montreal, QC, Canada
EDPE 676: Intermediate Statistics (Master’s and doctoral levels)
Descriptive statistics and distribution theories, sampling and sampling distributions, regression and
correlation, estimation and distribution of t, hypotheses testing for means and other statistics,
analysis of frequencies: 2, ANOVAs (one-way, two-way, and three-way), multiple comparison,
ANCOVA, repeated measurement, and simple regression
Jan. 2006
Teaching Assistant, McGill University, Montreal, QC, Canada
Univariate/ Multivariate Analysis (same content as Jan. 2007)
2004-2005
Teaching Assistant, McGill University, Montreal, QC, Canada
EDPE 684: Advanced Multivariate Analysis (same content as Jan. 2008)
2002-2003
Teaching Assistant, McGill University, Montreal, QC, Canada
EDPE 684: Advanced Multivariate Analysis (same content as Jan. 2008)
2000-2001
Teaching Assistant, McGill University, Montreal, QC, Canada
EDPE 682: Univariate/ Multivariate Analysis (same content as Jan. 2007)
EDPE 668: Item Response Models and Cognitive Assessment
Workshop and seminar series
Dec. 2012- 2014
Probabilistic modeling in bioinformatics
Application of Bayesian networks and probabilistic graphical models in learning sciences
Professional members
Bioinformatics Organization (BO)
International Society for Computing Biology (ISCB)
Cognitive Sciences Society (CSS)
Cognitive Neuroscience Society (CNSS)
Psychometrics Society
American Educational Research Association (AERA)
• Division D: Measurement and Research Methodology
• Division I: Education in the Professions
Southwest Educational Research Association (SERA)
Journal and paper reviewer
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AERA
Educational Measurement: Issues and Practice
Administrative Issues Journal: Education, Practice, and Research
The Journal of Experimental Education
Behaviour Metrika