Submissions / Doctoral Consortium
Doctoral Consortium: Call for Submissions
Please submit your application via easychair.org/conferences/?conf=isls2023 by 31 January 2023, 23:59 PST
Organizers & Contact
- Daniel Bodemer • University of Duisburg-Essen, Germany
- Xueqi Feng • Southern University of Science and Technology, China
- Erica Halverson • University of Wisconson-Madison, USA
Please contact Daniel , Xueqi or Erica for all questions regarding the Doctoral Consortium.
- 31 January 2023 • Applications due
- Mid-March 2023 • Notifications of acceptance
- Late March, 2023 • Submissions of the final abstract for publication due (camera ready)
- 10–11 June 2023 • Doctoral Consortium
- 10–15 June 2023 • ISLS Annual Meeting
The Doctoral Consortium, designed to support the growth of young talents working in the learning sciences or computer-supported collaborative learning (CSCL), provides an opportunity for advanced Ph.D. students to share their dissertation research with their peers and a panel of faculty serving as mentors. Participants will engage in collaborative inquiry and scholarly discourse to improve their dissertation work and to advance their understanding of the field. To benefit from the Doctoral Consortium, applicants should be advanced graduate students, and be at a stage in their dissertation research where the participants and mentors may be of help in shaping and framing the research and analysis activities.
The Doctoral Consortium (DC) aims to:
- Provide an opportunity for participants to reflect on their dissertation research and to identify problems/issues for discussion and inquiry;
- Provide a setting for participants to contribute ideas and receive feedback and guidance on their current research;
- Provide a forum for discussing theoretical and methodological issues of central importance to the learning sciences;
- Develop a network of supportive scholars in the learning sciences and in computer-supported collaborative learning across countries and continents;
- Collaborate and draw upon literature across countries and institutions;
- Contribute to the conference experience of participating students through interaction with other participants, mentors and organizers; and
- Support young researchers in their effort to enter the learning sciences / CSCL research community.
Doctoral Consortium activities are organized as a workshop with diverse participation modes. Participants will have opportunities to familiarize each other with their dissertation project and highlight specific aspects they would like to have further discussion on. Based on the common issues and themes identified (theoretical models, research design and questions, pedagogy and technology, data collection, methods of analysis, etc.) participants will receive support from expert mentors to engage in further inquiry and discussion. Participants will work on the various problems and issues identified, making reference to their own dissertation project and the broader field of the Learning Sciences or CSCL.
The Doctoral Consortium will involve a two-day event on June 10–11, 2023 during the ISLS Annual Meeting in Montréal, Canada. Financial support is available to offset some of the costs to attendees. More information will be provided soon. Prior to the workshop, a few preparatory activities are required to enable us to use the time within the workshop as best as possible.
Who should apply?
The Doctoral Consortium is open to those Ph.D. candidates who are most likely to benefit from the intended goals through collaborative interaction. Typically, applicants will have completed their dissertation proposal (or equivalent), and be at a stage in their work where consortium participation may be of help in shaping the design and analysis. If you are early in your program or you will have completed your dissertation at or around the time of the consortium, you should not apply.
How to apply?
Participants for the Doctoral Consortium will be selected on the basis of the academic quality of their proposal; relevance and potential contribution to the field of the learning sciences or computer-supported collaborative learning; recommendation from the advisor (supervisor); and their anticipated contribution to the workshop goals. The proposals will be reviewed by international experts in the field. An effort will be made to keep the participating group small to encourage interaction and collaboration.
To apply, please submit one PDF document containing the following three sections:
- A cover sheet with your name, title of your research project/ dissertation, your advisor’s name (or thesis chair’s name, as appropriate), your institution, your personal webpage, your e-mail address, and your mailing address.
- A one-page personal statement that includes: (a) a little about yourself; (b) current status of your research and studies; (c) why you want to participate in the DC; (d) what specific issues or challenges with your research you would like to explore further. You do not necessarily need these as headings, as long as the issues are addressed.
- A two-page summary of your research including tables, figures and references using the ISLS Template and following ISLS Author Guidelines and ISLS Submission Tips. The summary should include: (a) Abstract; (b) Goals of the research; (c) Background of the project; (d) Methodology; (e) Preliminary or expected findings; (f) Expected contributions. You do not necessarily need these as headings, as long as the issues are addressed. If accepted, you will be asked to revise your paper upon feedback from the reviewers before it can appear in the conference proceedings.
In addition, submitted through e-mail separately:
- A letter of recommendation from your advisor.
Please have your advisor submit the letter of recommendation directly to all organizers ([email protected], [email protected], [email protected]) in one e-mail using the subject “DC recommendation + <name of the applicant>”.
Please submit all papers in one file in PDF format. The application should be submitted via EasyChair at easychair.org/conferences/?conf=isls2023 by 31 January 2023, 23:59 PST.