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1. ASK CRame DROP-IN Student SESSIONS
1. ASK CRame DROP-IN Student SESSIONS
ASK CRAME sessions are for graduate students in the Faculty of Education seeking answers to contained methodological and statistical questions. These sessions are designed for graduate students to bring specific questions about design and analysis pertaining to their own graduate work. They are not a substitute for coursework or support from your research supervisor.
UPCOMING SESSIONS in ED N6-110:
Monday February 24th 10:00-11:30am and Wednesday March 19th 1:00-2:30pm.
Sign up here: https://forms.gle/d2NANAEz1ccDg2NJ8
2. Medical Education Research Assistant
Created in Fall 2024, the purpose of the DoM Medical Education Research Assistant (MERA) position provided by CRAME is to support Clinician Educators (practicing physicians who develop educational projects and/or lead education programs) with the necessary steps to conduct and disseminate their high quality work.
Ashely Clelland holds the DoM MERA position for the 2024-2025 academic year. In regards to the position, Ashley has the following to report:
Why were you interested in applying for the MERA position?
The MERA position tied into content areas that I'm passionate about, including innovation, assessment, and teaching and learning in the health professions. The position was also very diverse in terms of the research tasks I would be doing and the projects that I could potentially help to support. That diversity in opportunities was really appealing to me as an emerging scholar.
What do you hope to learn through the position?
I'm already learning a lot about medical education! It's an interesting discipline with a unique approach to teaching and learning, and I hope to keep learning more about that. I'm also hoping to learn more about conducting high-quality research in health-related settings, and strategies for communicating results effectively to health audiences.
What is your own favourite part of research?
It's hard to pick just one part because I love the whole research process. I really like doing data analysis, including both quantitative and qualitative work. It's an exciting part of the process because you start to see what you've found (or not found, which is also interesting!). I also like to write and come up with creative ways to share findings.
*If you have funding and would like to discuss the potential of establishing a dedicated CRAME RA, please contact the CRAME Director at lia.daniels@ualberta.ca
3. CONSULTATION FOR FACULTY MEMBERS
CRAME is pleased to release the following list of graduate students consultants. These students were selected for specific skill sets that are regularly sought out by faculty members across campus regarding methodology and analysis. Please read from the list of skills and directly contact a consultant to discuss your needs and their availability for paid work.
Tarid Wongvorachan
Tarid Wongvorachan
Methodological skills: Quantitative analysis (statistics, data mining, natural language processing), psychometrics, mixed methods research, citation management (Zotero)
Focal Area: Social science
Contact: wongvora@ualberta.ca
Augustine A Botwe
Augustine A Botwe
Methodological skills: Research design (quantitative, qualitative, and mixed methods), Community-based participatory research, action research; Quantitative analysis (statistics, data mining); Qualitative analysis; Psychometrics; Citation management (Zotero, Endnote)
Focal Areas: Social science, Maternal and Child Health, Early Childhood Development (ECD)
Contact: botwe@ualberta.ca
Surina He
Surina He
Methodological skills: Basic and advanced quantitative analysis (t-test; ANOVA and its’ variation; linear, logistic and multilevel regression; mediation; moderation; principal component analysis and factor analysis; structural equation modelling, especially analysis for longitudinal data); Educational data mining: basic machine learning, process mining; Educational and psychological measurement; Citation management (Zotero, Endnote)
Focal Areas: Social science
Contact: surina1@ualberta.ca
Bin tan
Bin tan
Methodological skills: Expertise in survey development, critique, selection, validation, and data collection; Statistical analyses for small-scale experiments (e.g., hypothesis testing for various experimental designs). Statistical analyses for mid- to large-scale data (e.g., structural equation modeling, machine learning, natural language processing)
Focal Areas: Social science, Patient-reported outcome measures
Contact: btan4@ualberta.ca
xiaoxiao liu
xiaoxiao liu
Methodological skills: Data Preprocessing (e.g., recode missing values, merge data), Quantitative analysis (e.g., t-test, regression, ANOVA, multilevel linear modeling, structural equation modeling), Educational data mining (e.g., k-means clustering), Machine learning, Data Visualization. Software programs such as R, SPSS, Python, Mplus, and HLM.
Focal Areas: Social science, Education
Contact: xiaoxia6@ualberta.ca
Kendra Wells
Kendra Wells
Methodological skills: Survey design; Data management; Experimental study design; Basic and advanced quantitative analyses including SEM and bifactor modelling; Meta-analysis
Focal Areas: Education, Educational psychology, Classroom assessment
Contact: khamp@ualberta.ca
Doris Abroampah
Doris Abroampah
Methodological skills: Machine Learning Algorithms in Predictive Analysis, Mixed Methods Research, Survey Design
Focal Areas: Education, Artificial intelligence in education
Contact: abroampa@ualberta.ca
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