This article acts as the second log entry of my 22-day stay in Dublin City University for my PhD thesis and possible research and project collaboration with the host research unit – National Institute for Digital Learning (NIDL) of DCU.
The second meeting was between the director of NIDL Mark and me and below I would like to share some notes from such conversation.
Meet: Prof. Mark Brown (http://www.dcu.ie/nidl/people/director.shtml)
Role: Director, National Institute for Digital Learning
Date: February 2, 2017
Time: 13:30 – 15:00
Mark introduced a little bit about DCU to me and was updating me about MOOC relevant research and practices at NIDL.
The conversation in general was loose, without agenda without a specific purpose. But a lot of interesting inspiration sparkled from this conversation.
Mark shared several books with me related to MOOC research.
About tool to do text analysis
Regarding the data analysis of my interview transcripts, Mark suggested me to read the following article to see if it can be of a help:
Zawacki-Richter, O., & Naidu, S. (2016). Mapping research trends from 35 years of publications in Distance Education. Distance Education, 37(3), 245-269.
Suggested tool: Text-mining tool Leximancer (http://info.leximancer.com/academic/)
Two interesting sites to visit
Make better decisions and improve service delivery with ECAR research and analysis. ECAR provides user data, higher education technology trends and practices, and collaboration opportunities for IT professionals and higher education leaders. ECAR is the only subscriber-driven research organization dedicated to improving IT’s contribution to higher education.
Pew Research (http://www.pewresearch.org/)
Inspiration to follow up
- DCU Age Friendly University (http://www.dcu.ie/agefriendly/index.shtml): Considering the social responsibility of university as an education center in the society, maybe MOOC can be also one way to engage the elderly people.
- Learners tend to avoid course entry survey. But using a more “sneaky”/hidden way like asking them to select from some scenarios and fill in some their own information in between, can help to benchmark the entry level and initial goal of learners before they started the MOOC.
- The learner types should be separated based on the engagement survey, and analyze these different types respectively.
- The MOOC instructor can put some student success tools in the first week or invite learners in advance before the MOOC starts, to help the learners to get ready for the learning journey with practical self-evaluation. The student success tools are open source code and anyone is free to use and customize.
- Analyze social media content relevant to a topic, such as Twitter contents analysis of ENTER conferences, EMOOCs conferences, etc.
Costello, E., Binesh, N., Brown, M., Zhang, J., Giolla-Mhichíl, M.N., Donlon, E. & Lynn, T. (2016). Social media #MOOC mentions: Lessons for MOOC mentions from analysis of Twitter data. Paper at ASCILITE 2016 conference. In S. Baker, S. Dawson, A. Pardo, & C. Colvin (Eds.), Show me the learning. Proceedings of the International Conference on Innovation, Practice and Research in the Use of Educational Technologies in Tertiary Education (pp.157-162), Adelaide, 29th November.
Costello, E., Brown, M., Donlon, E., Nair, B., Nic Giolla Mhichil, M., Lynn, T., Zhang, J., & Perris, K. (2016). Towards a research agenda of MOOCs in Twitter through analysis of a large dataset. Presentation at Association for Learning Technology Conference (ALT-C), Connect, Collaborate, Create, University of Warwick, 8th September.