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Evidence of Research Competencies

Synthesize related literature and locate gaps for potential research

I have completed three literature reviews during my doctoral studies. I conducted my first literature review in R711-Readings in IST to explore the application of natural language processing (NLP) in supporting learning. The first literature review helps me to locate discourse in computer-supported learning environments as my primary interest. The second literature review is conducted during R695-I. It furthermore explores one specific area of supporting collaborative learning - socially shared regulation of learning (SSRL) and identifies the gaps in studying teacher facilitation in supporting SSRL under the CSCL context. The second literature review prepares me with the theoretical framework for my first-author study. The third literature review is over conversation analysis, which supports me with the methodology foundations of my first-author study.

NLP for LEARNING

Support SSRL

Conversation Analysis

Utilize research methods in appropriate contexts

While completing my coursework and research projects, I have engaged in multiple research methods, collecting and analyzing various types of data.

For an example of qualitative research, I conducted teacher interviews for a case study with college teachers to know their challenges under the pandemic and facilitated and analyzed focus group sessions (participatory design) for K-12 teachers to collaboratively design orchestration assistants. I have been coding and analyzing interview data (thematic analysis), as well as classroom chat data (computer-mediated discourse analysis & interaction analysis). In my first-author study, I adopted conversation analysis to capture the strategies teachers applied to support SSRL in CSCL by looking at the naturally occurring data through talk-in-turn.

Conversation Analysis

For an example of quantitative research, I conducted inferential tests to analyze collected survey responses of self-directed learning in Tango learners and teachers. For collaborative learning, unsupervised machine learning method clustering was applied on coded game chat to explore individual behavioral patterns in groups

Inferential Tests

Clustering

Understand appropriate methods of inquiry in research

I aim to equip myself with both quantitative and qualitative methods as preparation for handling interdisciplinary research questions with different approaches.

Utilizing my minor in Methodology Inquiry, I have taken Y631 Discourse Analysis to prepare for my first-author study. I have taken both quantitative and qualitative methodology courses in the coming semesters, including Y650 Machine Learning Method for Education and Social Science (Spring 2022) and Y633 Feminist Theory & Methodology (Spring 2022). To pursue interests in technology with research methodology, I took Y616 Digital Tools in Qualitative Research (Summer 2022).

Course syllabuses are linked below.

Write research proposals; design and execute research studies

I have been working with Dr. Glazewski, Dr. Brush, and Dr. Hmelo-sliver in the joint of Big Data and i-ACT. In the project, I have helped modify IRB documents, prepared research protocols, implemented data collection in local schools, and managed data afterward.

Besides, collaborating with Dr. Bonk and my peer Zixi Li on exploring self-directed learning in Tango Dancers, we have drafted research proposals, submitted IRB for approval, designed online surveys, conducted pilot studies, and implemented data collection in the community.

Develop scholarly writing and presentation skills

I have been actively involved in submitting conference proposals and presenting at international conferences.

Feng, C., Saleh, A., Bae, H., Glazewski, K.., Hmelo-Silver, C. E., Brush, T., Mott, B. W., & Lester, J. (2021, November 2-6). Exploring Strategies to Redirect Disruptive Talk in Middle-school Collaborative Inquiry Discourse [Paper presentation]. Association for Educational Communications and Technology (AECT) International Convention, Chicago, IL, United States.
Bae, H., Saleh, A., Feng, C., Glazewski, K.., Hmelo-Silver, C. E., Brush, T., Mott, B. W., & Lester, J. (2021, November 2-6). “just vote yes.*sigh*”: Facilitating Scientific Discussion in a Collaborative Problem and Game-based Learning Environment [Paper presentation]. Association for Educational Communications and Technology (AECT) International Convention, Chicago, IL, United States.
Saleh, A., Feng, C., Bae, H., Hmelo-Silver, C. E., Glazewski, K. D., Lee, S., Mott, B., & Lester, J. (2021). Negotiating Accountability and Epistemic Stances in Middle-School Collaborative Discourse. In Hmelo-Silver, C. E., De Wever, B., & Oshima, J. (Eds.), Proceedings of the 14th International Conference on Computer-Supported Collaborative Learning - CSCL 2021 (pp. 197-200). Bochum, Germany: International Society of the Learning Sciences.
Feng, C., & Xu, Y. (2020). Case Study of Collaborative Learning in a Massive Open Online Course. Proceedings of 2020 Ninth International Conference of Educational Innovation through Technology (EITT), 47–51.
Feng, C., Rodgers, K., Bhimdiwala, A., Gok, S., Glazewski, K., Hmelo-Silver, C., Brush, T., Lee, S., Mott, B., Lester, J. (2020, November). Supporting teacher orchestration of collaborative inquiry in game-based learning with intelligent assistants [Paper presentation]. Association for Educational Communications and Technology (AECT) International Convention, Virtual.
Bae, H., Saleh, A., Feng, C., Glazewski, K., Hmelo-Silver, C. E., Chen, Y., Scribner, A., Brush, T., Mott, B., & Lee, S. (2020). Designing Intelligent Cognitive Assistants with Teachers to Support Classroom Orchestration of Collaborative Inquiry. In M. Gresalfi & I. S. Horn (Eds.), The Interdisciplinarity of the Learning Sciences, 14th International Conference of the Learning Sciences (ICLS) Volume 4 (pp. 2101-2108). Nashville, Tennessee: International Society of the Learning Sciences. (Nominated for Best Student Paper Award)
Feng, C., Law, N. (2019, Mar) Understanding Learning Design Studio Pattern Language through Implementation [Paper presentation]. Instructional Systems Technology Conference, Bloomington, IN, United States.

I have also co-authored with my team on the book chapter.

Uttamchandani, S., Bae, H., Feng, C., Glazewski, K., Hmelo-Silver, C., Brush, T., Mott, B., & Lester, J. (in press). Teacher orchestration systems supported by AI: Theoretical possibilities and practical considerations. In F. Ouyang, P. Jiao, B. McLaren, & A. Alavi (Eds.), Artificial intelligence in STEM education: The paradigmatic shifts in research, education, and technology. CRC Press.