Candidate Statement

My research interest lies in investigating ways to help learners take a concrete and meaningful approach to an abstract and complex problem in computer science. The content area of my interest centers on computer science concepts and principles; for example, understanding and applying computational thinking concepts or problem-solving algorithms used in computational machines. These subjects are often entangled with unfamiliar notions and notations to novices, making them difficult to understand and often incur misconceptions (Kaczmarczyk et al., 2010).

I believe these challenges could be addressed by employing approachable representations in which learners approach the knowledge structure of computer science easily when acquiring new concepts and skills or adapting to unfamiliar environments. With the aid of technology, representational systems can be adjusted to learning outcomes, targeted tasks, learner characteristics, and learning environment. Interacting with the knowledge structure represented to their level, learners could develop their understanding of complex concepts and engage in authentic problems and generative processes.

One of the ways that could provide an accessible representation to learners is to offer visual aids. From simple pictures to flow charts and advanced graphic organizers, visual guidance helps learners build a cognitive model by envisioning concrete structures or conceiving ideas in relation to other pertinent elements. They assist learners in establishing a deep knowledge base that can be applied in computational problem solving (Weintrop & Wilensky, 2017). An example of a visual representation in computer science education is to use block-based programming to introduce coding experience for novices. In addition, visual representations can also be effective for collaborative learning since spatial information helps communicate one’s cognitive models or solutions to others (Suthers & Hundhausen, 2003). For example, it is well established that a group graphic organizer can augment the quality of online discussions. In sum, my research is driven by two forces: computer science education and accessible representations of knowledge structure.

Specifically, my area of interest includes (a) teaching computer science using accessible representational systems, especially for computational thinking and artificial intelligence at the K-8 level; (b) broadening participation in computing and enhancing diversity, equity, and inclusion in computer science education, and (c) investigating affordances of representational guide in collaborative knowledge construction.

A. Computer Science Education: Towards Computational Thinking and Artificial Intelligence

Computer Science (CS) education has gained popularity in recent years. There have been numerous attempts to integrate CS education into the K-12 curriculum through enforcing legislation, developing standards and curriculum, and engaging teachers in professional development (Webb et al., 2017). Computational thinking (CT) is a psychological construct that enables computational problem-solving. In practice, CT concepts are used as core principles in introducing CS to novices. As CS education is closely aligned with technological trends and their applications in society, it is inclined to reflect and incorporate novel scientific progress and emerging technologies. Artificial Intelligence (AI) is considered to be one of the areas most vigorously pushed forward and influential technologies of our times. Despite the prominent use of AI technologies in our everyday lives and more to come in the future, AI wasn’t broadly addressed in K-12. Though many initiatives are making efforts to expand the opportunities to learn AI in K-12 (e.g., Computer Science Teachers Association, Association for the Advancement of Artificial Intelligence), practical guidelines at a school or classroom level are still scarce. Given that early exposure to STEM is related to one’s self-efficacy, attitudes, and career interests for STEM, it is worth expanding our efforts to introduce developmentally appropriate CT and AI education to young learners (Tran, 2018).

My research in CS education is concentrated on the understandings of AI and CT principles at the K-8 level (ages 6 to 14). Pertaining to AI education, I have been involved in a PrimaryAI Research Group (PIs: Drs. Glazewski, Leftwich, & Hmelo-Silver) and assisted in designing an inquiry-based learning curriculum that encompasses algorithms and applications of AI, biological sciences, and CT concepts. In the PrimaryAI research group, I got a chance to assist with the analysis of teachers’ interviews and interact with teachers during the professional development sessions. Through these experiences, I’ve learned more about the needs of the teachers and the students by identifying where they feel more confident or less, and how they perceive the novel changes brought by AI technologies around them. Working as a research assistant in the group provided insights on selecting and transforming content knowledge in light of prior knowledge, perceptions, and motivations of teachers and students (see Ottenbreit-Leftwich et al., under review). I’m also participating in AI Goes Rural Project where we seek to expand AI education in rural areas, in collaboration with middle school teachers (PIs: Drs. Kwon, Leftwich, & Glazewski). In this project, I aim to work on creating accessible representations for students and teachers with learning activities, manipulatives, and worksheets that help achieve a concrete understanding of AI concepts.

To accomplish my goal in CT research, I participated in the Google Computer Science Education Research Group (PI: Dr. Leftwich) and assisted in the design and development of the inquiry-based CS curriculum. Particularly, our team developed worksheets that led learners to visually describe the flow of their program to facilitate learners’ design and development of programs. We explored the students’ CT practice by analyzing their thought processes and patterns represented in their worksheets and Scratch programs (see Kwon et al., under review). In addition, from this experience, I investigated how to integrate CT into a K-12 curriculum, how to assess its learning outcomes in an upper elementary context, which was led into publications (see Kwon et al., 2021; Ottenbreit-Leftwich et al., under review).

Further, while serving in a teaching assistant position for an undergraduate course, EDUC-W220, I delved into how pre-service teachers’ CT practice evolved from a more approachable representation of a programming environment to an authentic programming language. This endeavor was led to a study that compared novice programmers’ CT practice across block-based and text-based programming languages (see Jeon & Kwon, under review).

I believe we need to make endeavors in translating the convoluted and intricate language of CS for teachers and students. I believe the most effective way of doing so is working closely with the teachers, knowing their needs, and reflect their pedagogical intuitions in designing AI curriculum, instructional materials, and guides (e.g., Könings et al., 2010; Lin et al., 2021). I plan to continue my research in this area by actively participating in the CS education research groups in IST.

B. Broadening Participation and Enhancing Diversity, Equity, and Inclusion in Computer Science Education

On top of exploring instructional strategies to better teach CS in K-12, I believe fostering diversity, equity, and inclusion in CS education is imperative to develop the young population’s future careers and meet the socio-economic demands of the country. To guarantee equal learning opportunities for CS, CS advocates from higher education, K-12, industry, and nonprofit organizations, are working toward broadening participation in computing (BPC). Expanding Computing Education Pathways (ECEP) is one of the initiatives that provide interventions and models to advance BPC efforts across states (ECEP, 2020). Working for ECEP alliances, I conducted document analysis of the ECEP’s longitudinal data and created an inventory that maintains a state of CS education for each state (see Jeon et al., 2021b). This work has allowed me to explore numerous state-level efforts in BPC, identify, and organize data sources. I also assisted in writing a research paper that describes a five-stage model that ECEP identified to help a state advance its BPC goals (see Ottenbreit-Leftwich et al., under review).

As a member of CSforIN, I created a dashboard that houses Indiana’s high school students’ enrollment in computer science-related courses and tracks the numbers of enrollees according to gender, ethnicity, and locale. It displays the extent to which student enrollment rates reflect the demographics of the school or district’s population. Further, I’m currently developing a research article that examines the relationships of enrollment rates and socioeconomic statuses such as family income, parents’ education level, per-pupil spending, and teacher salaries (see Jeon et al., in preparation). Aligned with my goals for service to the research community, I’ll continue to update the current state of CS education and make it a window for the betterment of CS education research and policymaking.

Together with the introduction of CS education standards and curriculum, we must ascertain that the teachers and administrators buy into them; if the new CS initiatives are mistakenly portrayed as threats to their status quo or if the costs associated with teaching CS are deemed too high, it runs the risk of lukewarm reception and hence challenges to prepare capacity to deliver CS instructions (Fletcher & Warner, 2021). A way to ameliorate anxiety on the part of the practitioners is to help them understand why CS education is important and develop their confidence and pedagogical knowledge. Aligned with my goals for service, I aim to participate in professional development or outreach programs for K-12 teachers and assist in creating teacher training modules that would encourage teachers to respond to current needs for CS education with enthusiasm. Looking ahead, I would like to examine the efficacy of the program on teachers’ practice in classrooms.

C. Representational Guidance to Promote Collaborative Knowledge Construction

As stated above, I’m interested in examining the effects of visual representation of information, as an instructional strategy. Representational guidance is known to be useful in improving the understandings of complex concepts as well as online collaboration (Kwon & Park, 2017; Suthers & Hundhausen, 2003). Technology convergence and collective intelligence require a holistic view and an ability to construct knowledge based on collaboration. Collaborative efforts, however, need to be regulated since they usually produce a large amount of information that involves various hands (Kirschner et al., 2008). Graphic organizers could help learners recognize information from diverse sources and manage group efforts. I took part in the CSCL Research Group (PI: Dr. Kwon) and reviewed the literature regarding groupware that coordinates the collective effort. Additionally, I created instructional materials for a graduate-level course and facilitated case-based reasoning activities. As my first authored study, I conducted an experimental study that employed graphic organizer authoring tools for asynchronous online discussions (see Jeon et al., 2021c). My colleagues and I revealed that the types of graphic organizers make a difference in collective knowledge construction. I intend to continue to verify the affordances of visual representations and ways to effectively apply them in instructional design.

For pre-service teacher education, I believe building content knowledge and pedagogical knowledge should be intertwined (Shulman, 1986). Teachers’ pedagogical knowledge can only be situated in the teaching contents and without a deep understanding of the discipline, it will be challenging for a teacher to connect the core ideas of a discipline and design meaningful experiences for learners.

Through taking IST courses about designing, developing, and evaluating instructions, I could gain both theoretical knowledge and hands-on experience for my design of a course. I created and taught a curriculum for an undergraduate course, EDUC-W210 Survey of Computer-based Education (Syllabus), one of the courses required for a computer educator license. When I was developing the curriculum, I could gain constructive advice from IST faculties who are experts in the field of instructional designs and CS education. They assisted me with embodying my teaching philosophy and infusing it into concrete learning activities and materials. I introduced students to CS topics like CT, algorithms, HTML & CSS, Scratch, and Robotics, and while doing so, the students were guided to actively engage in authentic and at the same time, education-specific design tasks, such as creating websites for educational programs, and classroom management applications. To enhance the students’ abilities in pedagogical content knowledge, I enabled them to create instructional materials for example Scratch applications for math and earth sciences.

To extend my teaching practice, I observed and collaboratively designed W200 classes and served as a teaching assistant for W220 and R521. When designing discussion activities for R521, the balance of content knowledge and pedagogical knowledge was maintained. With the use of a group’s graphic organizer, the students were encouraged to explore diverse themes and enhance their critical thinking skills by evaluating and reflecting on the ideas brought up by others. At the same time, as working with distinct types of authoring tools for creating a graphic organizer, the students reflected their uses in online learning settings and how to incorporate them in their instructions.

The areas of strength and areas for improvement in my teaching practice are identified as the following. One of my strengths as a teaching practitioner is that I have plenty of experience as a former educator in K-12 and a mentor for new teachers. The experience as a practitioner will help me understand the concerns of the pre- or in-service teachers and where they will be likely to have difficulties. I'm also capable of creatively adapting instructional designs tailored to learner characteristics. Further, I’m willing to continue to expand my knowledge of recent technologies and incorporate them in my class, which will help students discover recent learning technologies. Still, I admit that I need more teaching practice in higher education since my teaching experience is limited to one time as an instructor and two times as a teaching assistant. I also need an understanding of the K-12 education system in the country because that is the context my students will encounter as a practitioner.

I view service to academic and local communities as a valuable opportunity that I can contribute to the society that I belong to. I hope to spread positive influence on the communities through my research and teaching that bring attention to under-served populations in CS education and raises awareness for CS for all. This can be seen in my services at the local, state, and national levels. At the local level, I volunteered in outreach opportunities as an instructional assistant and supported coding clubs in elementary and middle school. At the state and national levels, I’m participating as an advocate for broadening participation in computing initiatives such as CS4IN and ECEP. In the annual conferences of the Computer Science Teachers Association [CSTA] and ACM Special Interest Group on Computer Science Education [SIGCSE], I, on behalf of our team, presented research findings of CS education policy to encourage teachers to join CS education initiatives and make their voices heard (see Jeon et al., 2021a; Jeon et al., 2021b). I've also participated as a moderator and reviewer for proposals for conferences like AERA and AECT, mostly evaluating the literature on CS education. Additionally, I've been taking a leading role in the past IST conferences as a leader in the tech support team from 2018 to 2020. I intend to contribute to the local and academic community as I move forward as an education scholar.