The following research group descriptions are archived because they are no longer offered, the faculty member is on sabbatical, or the group is taking a break. Please contact the faculty member or an advisor to learn more about these groups.
- A Systematic Literature Review of Concept Inventories for Introductory Computer Science Education
- Evaluative Study on Dataland - A System Designed for Novices to Analyze and Visualize Data
A Systematic Literature Review of Concept Inventories for Introductory Computer Science Education
Concept Inventories (CIs) are a well-documented tool in education research, generally defined as a set of questions which enable educators to identify not only the concepts students are struggling with, but also the specific misconceptions which they hold. This idea originated with the famous Force Concept Inventory in physics, which was first published in 1998 and led to a subsequent revolution in introductory physics education throughout the nation.
Computer science education researchers have been attempting to precipitate a similar revolution over the last 15 years. Efforts are ongoing, but still far from complete. The last thorough review of literature in the space of computer science CIs was conducted in 2014, nearly a decade ago. With many recent advancements in the field, it is important to once again review all the literature in an organized manner. The goal of this DRG is to prepare a systematic literature review of computer science concept inventories and aim for submission to the ACM Conference on International Computing Education Research (ICER 2023).
Objectives and Student Expectations
Students who join the DRG will receive the experience of working on a full research project with a concrete deliverable. DRG members will be expected to do the following:
Attend a weekly one-hour meeting to discuss individual and group progress and plan next steps.
Contribute to both reading and writing over the course of the literature review.
Dedicate at least 5 hours a week to searching, reviewing, and discussing the literature surrounding concept inventories in computer science.
Students will leave the DRG with a strong understanding of how to conduct a systematic literature review and write an academic paper, both essential and valuable research skills. Additionally, students will receive the opportunity to contribute to an academic research paper if interested.
The lead researcher on this project, PhD student Murtaza Ali, is also working on developing a tool which will concretely implement an existing concept inventory in Python and allow students to work through and slowly diminish misconceptions. There is a possibility that dedicated and interested students who show outstanding commitment in the literature review phase of the project will also receive the opportunity to contribute to the development of this tool.
Who Should Join This DRG?
We are looking for 8-10 students (grad or undergrad) who meet the following qualifications:
Programming experience equivalent to one introductory course (formally known as CS1). While you will not need to program in this DRG, familiarity with basic computer science concepts is essential for understanding the literature surrounding computer science CIs.
Note: Introductory computer science students are especially encouraged to apply, as you can apply your own experiences with misconceptions to the work.
The ability to commit to at least 6 hours of work a week (including DRG meetings).
Strong reading and writing skills, with the willingness to actively work on improving these skills. It is not strictly necessary that you have experience with research papers specifically–interest in the subject matter is more important.
Evaluative Study on Dataland - A System Designed for Novices to Analyze and Visualize Data
In today's increasingly data-driven world, it is important for young people to learn with and about data. However, existing programming and data analytics systems are not designed with the consideration of young people’s competencies and interests. How can we design to support young people to ask and answer questions with data in creative, engaging, and personally empowering ways?
To answer this question, we have developed a visual block-based programming system - “Dataland” - for novices to analyze and visualize data. More information about the system can be found here: https://learning-with-data.github.io/. In this directed research group (DRG), we will: (1) conduct internal testing sessions on Dataland and address any issues, and (2) run research workshops with 8-17 year olds to evaluate Dataland.
This DRG will be led by Dr. Sayamindu Dasgupta and PhD student Regina Cheng. The group will be run for 3-6 dedicated undergraduate students. The course will provide 2-5 HCDE 496 course credits, with the expectation that students will spend approximately 3 hours per week per credit. This DRG will be hybrid with a combination of virtual and in-person meetings. We will meet at a time that is convenient for all the students.
Prerequisites: Strong speaking, reading and writing skills in the English language, a computer you can use during the project, ability to attend team meetings through an online conferencing platform or in-person, and a commitment to high-quality research are required. Willingness to work both in a team and independently is required. We strongly prefer candidates with passion and experience in usability testing, interview, and qualitative methods. Students do not need to have any prior experience in data science and programming.