Background. U.S. state and district policies increasingly mandate computer science (CS) instruction in K-12 classrooms. To ensure all students benefit from computing education, we recognized the crucial need for teachers to adopt equity-focused practices. Leveraging a researcher practitioner partnership (RPP), we launched a pilot program providing teachers with individualized coaching.

Generative AI presents many possible use cases in the context of education research, including summarizing previous research, creating literature reviews, generating synthetic data, analyzing qualitative as well as quantitative data, creating data visualizations, and writing research papers. However, there are also many ethical issues that may arise related to the use of generative AI, including concerns related to environmental impact, human impact, data privacy, transparency and replicability, the potential for data re-identification, intellectual property and intellectual debt, the digital divide, and accuracy and bias. In order to promote the responsible use of AI in education research, we formed a group with expertise across the relevant research practices and ethical issues to convene in order to articulate guidelines for the use of generative AI in STEM education research.

In a recent pilot study, we investigated computer science (CS) motivation among middle school students through multiple lenses: identity, interest, value, communal/agentic goal affordances and endorsements, sense of belonging, self-efficacy, and intentions to pursue CS. Our research question was: What are the motivational differences to learn computer science among boys and girls in middle school? We collected data from three U.S. sites (California, Michigan, and Illinois) in Spring 2025. We conducted an independent-samples t-tests to ascertain gender differences in each type of CS motivation. While significant results were found across three measures (value for CS, communal goal endorsements, and intentions to pursue CS), the remaining measures did not produce significant differences, indicating that boys and girls may have similar CS identities, interest in CS, sense of belonging in CS, and self-efficacy.

The Computer Science (CS) Professional Development (PD) Passport Alliance has created an addition to the Computer Science Teachers Association (CSTA) member platform that provides the capability for CSTA members to track their CS PD-related activities in one convenient place. As part of our research effort supporting the platform development, one of our research questions was: Among teachers, what features or practices are associated with trusting in software that contains professional personally identifiable information (PII)? We conducted an exploratory mixed methods study (teacher interviews n = 17, teacher survey n = 495, program evaluation survey n = 494) to determine what enables trust in software that stores professionally identifiable information and which features were most important to teachers future use of the platform. We provide recommendations for the project implementation team (such as adding multi-factor authentication to the platform) to mitigate risks of a data breach (which our survey indicated would impact 98% of the respondents' perceptions).

Background. The Standards for Computer Science (CS) Teachers include indicators related to classroom practices. To assess teacher proficiency related to these indicators at scale, we created and pilot-tested a vignette-based measure of K-5 CS teacher proficiencies related to Standards 2, 4, and 5.

In the current socio-political climate, computing educators are facing increasing challenges, including threats to academic freedom, reduced funding for higher education, and direct attacks on initiatives supporting diversity, equity, and inclusion. This special session offers an inclusive forum for collective reflection on these pressures. Through facilitated discussion, participants will explore emerging patterns, share practical strategies for navigating institutional and policy constraints, and surface both shared concerns and context specific differences. The session aims to strengthen community connections and support educators in sustaining inclusive, high quality computing education amid ongoing uncertainty.

We developed a 1.5 year coaching program to provide sustained support for newer U.S. high school computer science (CS) teachers, aiming to foster their knowledge about CS and CS practices and strengthen their confidence as CS educators.This study addressed the research question: How do teachers' abilities and confidence in applying computer science (CS) practices and concepts change as a result of the coaching process?We collected participant data across three timepoints, prior to the start of the coaching sessions, after the first year, and after the final coaching sessions.These results may indicate preliminary evidence that the intervention successfully increased CS coachees' reported knowledge and skills and their confidence as a CS teacher.

What does it mean to conduct computer science education research in a manner that ensures that the evidence produced is high quality and benefits a wide variety of students? One can pour over various guides from institutions like What Works Clearinghouse (WWC) and the American Psychology Association (APA). However, what many standards fail to include is a holistic perspective of conducting education research, including guidelines for ensuring that the aggregated data presented represents the student population that the research will ultimately serve. In this panel, we tackle both and explore approaches that have been used in other education research fields as well as those appropriate to CS education research that can be leveraged to ensure that all students' needs, experiences, cultures, identities, and voices are captured and presented in our research.

We designed a one-year coaching program to provide U.S. high school CS teachers with the ongoing support to help shape their professional growth and identity as CS teachers. Our research question for this project was: Does CS coaching facilitate teacher professional growth and identity as a CS teacher? Adopting a mixed-methods approach, our study leveraged pre- and post-program surveys, ongoing coaching logs, and introspective self-reflection checklists to triangulate data from both coaches and coachees. Coachees' rated their professional growth and identity significantly higher after the intervention compared to before, and this difference indicated a large effect. Both before and after intervention, coachees indicated they identified partially as CS teachers, and this sense of identity grew after intervention. The success of this pilot, rooted in effective professional development practices, demonstrates how engaging teachers in coaching can motivate their interest in teaching CS. Professional development providers and regional agencies can replicate and adapt these processes to empower new CS educators.

Promoting equity in computer science is crucial, but how best to measure equity is not entirely clear. Building on the tradition of critical quantitative inquiry, we present a test case of four different ways to measure equity in undergraduate CS programs for a given target population: the count of the population, the percent of the population in CS (as opposed to in other majors), the percent of CS students from the target population, and a metric we introduce, the proportional representation index (PRI). The PRI mitigates the impact that very large schools, very large CS programs, and regional population variation can have on the other metrics, but it also presents its own challenges. We believe that this work will contribute to the conversation regarding measuring equity by presenting and then problematizing several possible metrics.

In recent years, eight states have adopted a graduation requirement in computer science (CS), and other states are considering similar requirements. Due to the recency of these requirements, little is known about student and teacher perceptions of course(s) that fulfill the requirement and their content. This project seeks to answer the question, What are the perceptions of students who are studying CS beyond high school and CS teachers of a high school CS requirement and its content?

Despite their shared goal of improving learner outcomes [6], a persistent gap often exists between practitioners and education researchers. Team building within a Research Practice Partnership (RPP) requires leadership and team members that are not only committed to working together but also have the proper tools to do so. Thus, our research question is, What would an analysis of strengths, weaknesses, opportunities, and threats (SWOT) reveal about the formation of an RPP against Dimension 1 of the Five Dimensions of Effectiveness Framework? We conducted a series of interviews with RPP members every six months of the course of three years, conducting six sets of interviews in total with participating members of the RPP ranging from n=7 to n=12 participants.

Although there is extensive research on what makes K-12 teacher computer science (CS) professional development (PD) effective, little attention has been given to how PD providers prefer to collect and report data. A platform that met the needs of teachers while also simultaneously meeting the needs of funding bodies could be powerful in answering questions about participation and experiences in CS PD. Our research question for this study was: Which features and types of data do teachers find most important to include in a platform designed to record data related to their engagement with PD? We used an exploratory-sequential mixed methods approach that included focus groups and a survey created from an analysis of the data from the focus groups.

The session will present the final report of an NSF sponsored workshop tasked with creating a vision for computing education for the next 15 years. Within several broad themes identified, the panelists were asked to probe further into where the field should be heading and what difficult questions we need to tackle. We will use the final report as a basis for discussion with the attendees and ask them the same hard questions we asked ourselves when writing this report to see how these questions shape their views of where computing education needs to be in the next 15 years.

BACKGROUND. This full research paper focuses on understanding research foci (what) and student participants (who) in primary and secondary (K-12) computer science (CS) education research (CER). With the growing interest in CS education at primary and secondary schools, there is a growing body of research. Unfortunately, there is limited analysis of research against the broader education ecosystem. Given the significant contributions in CER in the U.S. and the United Kingdom, a comparative analysis of research between the two regions can identify strengths and opportunities for each. RESEARCH QUESTIONS. Our research questions for this study were: When comparing using the CAPE framework, what similarities and differences across areas of study exist among research studies with student participants from the UK and the U.S. ?and What similarities and differences exist in reporting of participant demographics between studies with student participants from the UK and the U.S.? METHODOLOGY. We conducted a systematic mapping review of K-12 CS education research publications (2019–2022). We used the Capacity, Access, Participation, and Experience (CAPE) framework to group publications that studies similar topic areas. We then ran descriptive statistics (counts and percentages across number of codes and also number of publications) to identify commonalities and differences between the regions with respect to areas of focus and student participant demographics, FINDINGS AND IMPLICATIONS. Our results suggest that dominant-norming likely exists in our corpus of CER that needs mitigating. Studies with UK participants reported prior experi-ence and gender of participants significantly more, while those in the US were twice as likely to report participant race/ethnicity significantly more. Research focused on pedagogy, the topics of student engagement, and content knowledge were studied more frequently than other areas in both regions. There is limited research related to funding for computing education, school-based extracurricular activities, and social-familial influences, all of which are critical for understanding their impacts on students.

While there are multiple standards bodies that define characteristics of high-quality, there are limited guidelines on conducting equity-enabling research, particularly in the context of high quality and in computing education. As part of an ACM ITiCSE Working Group in 2023, we engaged in a concept analysis and structured literature review to identify high-impact practices for conducting both high-quality and equity-enabling education research. As a result of this work, we produced a set of guidelines across each major phase of research that integrates characteristics of high-quality education research with those that are necessary for producing research that is designed to honor and meet the needs of various subgroups of learners. Special emphasis is given to the role that the researcher plays in shaping the research based upon how the researcher's lived experiences, perspectives, and training influences their work. During this special session, we will review each set of guidelines and engage attendees in reflection and discussion of them and how they can use the guidelines to enhance their education research.

Problem. Understanding computer science (CS) teacher CS knowledge primarily relies on self-reported data from participants to understand the learning impact on teachers and improve teacher growth. There is currently a lack of quality instruments to determine where CS teachers need to improve their knowledge.

Correcting the under-representation of people with disabilities in computing and computing-related careers will require a research base that enables equitable computing education (CE) for all students. For this study, we analyzed research papers in order to better understand the landscape of CE research as it relates to students with disabilities. Of the 771 papers reviewed from 12 major CE venues over the last decade, very few (n = 14) specify student participants' disability status; this <3% rate is under-representative, given that about 15% of students in the US have a disability. Studies that do specify disability status tend to involve students who are in the middle grades, in the United States, and/or are participating in elective activities. Demographic factors (e.g., gender and race) are specified about half of the time and analyzed about half as often as they are specified. A small cadre of researchers (51 from 22 different institutions) are responsible for the studies specifying disability status. Studies - whether they specify disability status or not - most commonly use block-based programming, which may present accessibility issues for some students. Advancing equity for all students will necessitate much more research on the computing experiences of students with disabilities, including reporting factors such as demographic data that make it easier to determine whether and how the research applies in a given context. More research focused on accessible tools and languages for learning computing is also needed to further understand promising practices for teaching students with disabilities.

Traditionally, computer science (CS) in the United States has been an elective subject at the high school level. In recent years, however, some school systems have created a CS graduation requirement. Designing a required CS course that meets the needs of anticipated future advancements in the field necessitates exploring the research question, What computing content do high school teachers, college instructors, and computing industry professionals prioritize in a required computer science course for high school students? To better understand what these different groups perceive to be the essential content of a foundational high school CS course, we conducted a series of focus groups. These focus groups explored participants' (n = 21) thinking about what content would be most important to prioritize in a required high school CS course. Transcripts of the focus groups were abductively coded and then analyzed to determine what CS content priorities were identified and what disagreements about priorities exist.

Problem. This full research paper describes the results of a literature review of data collected about K-12 computer science education research and initiatives. Over the last ten years, K-12 computer science (CS) education research has evolved to meet the needs and progress of the computer science education community. As a field, however, we have no empirical evidence of what this evolution is and how it has managed to produce the empirical evidence needed to support the long-term goals of computing education research as computing education grows into every primary and secondary classroom. Research Question. Our question for this study was How has K-12 CS education research evolved over the last decade, including when examining the research based on standards and inclusion of student participants? Methodology. Using a publicly available database of curated articles documenting K-12 computing education research efforts, queries were run to extract pre-specified subsets of data. Descriptive statistics were calculated to identify trends to support answers to the research question. Findings. We consider how this data reflects on changes in the last decade in light of the CS for All initiatives, including the fact that less than 5% of studies include students with disabilities and less than 20% of studies report participants' socioeconomic status. With the growth of computing in schools in the last decade, it is important to consider previous computing experience of students when analyzing results, but our data shows that only 40% of studies do. Implications. The good news is that this increase means that more topics, contexts, and student subgroups can be explored each year, and new insights on best practices are likely to arise from these findings. The bad news is that the attention to the needs of historically marginalized groups is not increasing at the same pace. While our data shows modest to gradual increases in the percent of research articles that report on factors such as the student race and instructor gender, these factors are still rarely reported, which may make it more difficult to ensure that CS education research involves a wide diversity of participants.

Industry trends showcase the increasing importance of soft skills, but interpersonal STEM education is not yet well defined [7, 14]. With high technology churn and increasingly higher-level programming practices, the need for effective collaboration remains constant, as "productivity depends on a work force that is socially and emotionally competent" [5]. Social and Emotional Learning promotes engagement in STEM [1, 6], while experiential/makerspace learning increases equity, belonging, and competency [3, 13, 19]. Reflecting on undergraduate Agile [2] Software Development at Knox College, we contend that learning to make Software is less important than learning to work together while attempting to make Software. We define Soft-Aware Development to encompass building Software, building stakeholder relationships, and building up each developer along the way.

To investigate and identify promising practices in equitable K-12 computer science (CS) education, the capacity for education researchers to conduct this research must be rapidly built globally. Simultaneously, concerns have arisen over the last few years about the quality of research that is being conducted and the lack of equity-focused research.

This workshop aims to help individuals expand their engagement with the computer science education research community as inclusive and equitable peer reviewers. Peer reviewers are liaisons between a journal or funding organization and members of their professional community, and thus are crucial for incorporating equity as part of the culture of computer science and engineering education. Prior research has shown that being a peer reviewer has benefits for the reviewer as well as the journal. Peer reviewing journal articles and proposals is a good way to stay current with what is happening in the field and acquire insights that can improve one's own writing and research. Peer reviewing is also a way to promote equity in our community through inclusive practices. Inclusive reviewing practices provide respectful, constructive feedback to authors on aspects of their manuscripts and proposals such as bias-free language, treatment of vulnerable populations, and positionality of authors and reviewers. This workshop (supported by NSF grants EEC-2037807, 2037788, and 2037797) prompts participants to consider their own positionality as reviewers and scholars. From this perspective, they then consider important aspects of an article or proposal such as whether underserved communities are impacted by the work, if participant identities are referred to appropriately, if authors of color working in this space are being cited appropriately, and if authors are being accountable to do the challenging work of addressing issues related to diversity and equity.

A recent study found that there is a litany of unmet needs that are serving as barriers for the CS education research community to grow in depth and breadth, including ensuring that the community is representative of the teachers and students that are studied. Cultivating a diverse, equitable, inclusive, and accessible CSEd research community requires simultaneous bottom-up and top-down alignment on practice standards, professional development, and wellbeing for all constituents that is rooted in politicized trust and collective impact. For this position paper, we engaged in an expository writing process using a confirmatory and elucidating research design to contextualize quantitative and qualitative data reported from our previous study within related work. Our results indicate that there is a variety of researcher-centered, researcher-adjacent, and research-centered barriers in CS education that affect researchers' practice, and personal and professional identities. These results were validated by findings from research in other fields, such as education, psychology, and organizational change. These findings highlight the need for intentional changes to be made, both top-down and bottom-up, to sustain and grow the CS education research community in a way that equitably supports the evolving needs of a diverse set of students as well as the diverse set of researchers who study interventions.

Professional learning programs for computer science (CS) teachers primarily rely on self-reported data from participants to understand the learning impact on teachers and improve teacher growth. We developed and piloted a set of standardized measures of teacher growth aligned with Standards 2-5 of the Computer Science Teachers Association (CSTA) Standards for CS Teachers. We created a rubric from the 29 indicators across the four standards by merging similar concepts. We reduced these 29 indicators into 18 rubric items placed in one of three groups: Planning (9 items), Assessing (3 items), and Professional Development (6 items). We also created scales for measuring progress on each item based on the criteria for each standard. After creating an entry form based on the rubric items, we conducted a two-cycle pilot process, with teachers (n=24) completing the entry form and providing feedback in the form and in focus groups. We then applied revisions to the process, and conducted a second pilot with a different set of teachers (n=29). Teachers reported multiple ways to improve the process, including understanding their own growth path as a CS teacher. In this experience report, we describe the process of creating the rubric, the two-phase pilot used to gather feedback from the teachers, and the changes that we made to the rubric based on teacher feedback. We also provide a high-level description of the 18 items in the rubric, lessons learned, and recommendations.

Research Problem. The CAPE Framework has been used in multiple studies to situate capacity-building efforts within schools to offer equitable student access to and participation in K-12 computer science (CS) education. CAPE defines four major components of capacity, access, participation and experience. However, to define what each of the CAPE components can entail, well-defined subcomponents are needed.

Have a CS education research project that needs a survey? If you're an education researcher who wants to learn more about survey instrumentation in order to expedite and improve your research, this session is for you! Come learn how to find, remix, and use existing surveys by delving into the process of taking openly shared resources and repurposing them for your projects. In this workshop, we'll cover basics of survey creation and modification, as well as touch upon some additional useful tips like piloting surveys, how to avoid bots attacking your survey and protecting your participants' privacy. We'll also look at how to choose a survey that fits your needs. You will be actively engaged in hands-on activities. Key takeaways from this workshop will include clear steps you can take to choose an instrument that addresses your research questions and study design, the role that validity and reliability play in instrument design, how to modify an instrument (if needed) to answer your research question, and how to add your instruments to the corpus of instruments at the K-12 CS Education Research Resource Center. Laptop is needed for this workshop.

Motivation. There are countless factors that contribute to academic achievement [3, 6, 7, 8]. For K-12 computer science (CS) education, these building blocks of student success are broadly captured in the four components of the CAPE framework, which considers the capacity for, access to, participation in, and experiences of students learning CS through a lens of diversity, equity, and inclusion [4]. However, there is currently little published research that identifies factors within each component that influence the education ecosystem that students rely on to participate and have positive learning experiences in CS [10].

Problem. Diversity, equity, and inclusion (DEI) need to be embedded throughout the computer science education (CSEd) research community in order to achieve empirically-based strategies in CSEd that is responsive to the needs of all of its constituents. However, there are no comprehensive studies that investigate what the barriers and challenges to DEI are among CSEd researchers.

The session will present an overview of findings of a recently funded NSF workshop that set out to examine the pressing issues for computing education research for the next 15 years. Based on dialogs for scholars working in this area, the workshop participants developed a series of themes and topics that they felt should become the focus of computing education research efforts for the next 15 years. Main themes that emerged and will be discussed in this session include: diversity, equity, inclusion, ethics, broadening participation, teaching, learning, K-12, research to practice, computing's connection to other fields, and computing education research disciplinary issues. The session will focus on interesting research questions from each of these areas that are ripe to be explored as well as enablers and blockers to the progress of this work.

In this special session, we present tools and resources created from educational theory to make teaching and scholarship easier and more effective. Included in these resources are CS Teachers Association, CSforAll, CS Teaching Tips, CT Pathways Toolkit, EngageCSEdu, CS Assessments Hub, Cybersecurity, and CS Ed Research Resource Center. These tools/resources provide assistance at the district and school level (administrators, curriculum designers), classroom level (teachers), and researcher/evaluator level. In addition to these overviews, we will provide information on where to find them and will leave ample time for questions from attendees.

Engaging teachers in research has been shown to increase their self-efficacy and other factors related to increasing students' learning and growth. In this project, we partnered education researchers with computer science (CS) middle school teachers in the U.S. to develop a set of equity-focused teacher practice briefs that address a problem of practice that the teachers experience in their classrooms. Using a prescribed development process previously developed by Bell and Rhinehart (2016) for creating these briefs, teacher involved in the process saw their self-efficacy, professional networks and pedagogical content knowledge with respect to equity increase. The process allowed educators to reflect on their understanding of their particular problems of practice, while also collaboratively with expert researchers in the field to interpret previously published research results. The teachers and researcher teams created three briefs for the broader community to use. Throughout this four-month process, we learned how to improve the format for our particular needs, which included ensuring all voices were heard and equity was at the forefront of the work. In this experience report, we detail the process we used and report on lessons learned about the process from the teachers and researchers who participated. We also provide recommendations for others interested in using this method to engage in-service or pre-service teachers.

Is quantitative data collected by CS education researchers objective? If we combine data from a set of studies that measure the same type of intervention, will that really show us the strength of that intervention? Are qualitative studies really less rigorous than quantitative because the number of participants may be as low as one?

Problem. K-12 teachers face many challenges when teaching a new subject like computer science (CS). They are often far removed from the research being conducted to identify evidence-driven solutions to these challenges. Likewise, researchers are also often removed from the challenges of classroom practices that teachers face when teaching CS. Research Questions. To create a collaborative process for teachers and researchers outside of a research practice partnership, we piloted a facilitated process in which CS middle school teachers and CS education researchers collaboratively created CS teacher practice briefs. Our research question for this study was: In what ways are teachers impacted by the process of creating teacher practice briefs in collaboration with researchers? Methodology. We conducted a qualitative study, using a semi-structured interview protocol to interview five teachers and three researchers to gain an understanding of how this process impacted the participants. We used thematic content analysis to identify several subthemes across our pre-established themes: motivation for teachers to participate, impacts on teachers, perceived impacts on students, and impacts on researchers. Findings. We found that the impact on teachers mirrored impacts found on teachers who engage in Research Practice Partnerships, including increased self-efficacy, expanded professional networks, and changed classroom practices. Implications. By bringing researchers and educators together with a clear focus on equity-based problems of practice in CS education, the results display a multitude of positive impacts. Teachers indicate that they are are positively impacted, researchers develop a clear understanding of realistic practices, and students are peripherally impacted through changed practices in the classroom. Therefore, the most significant contribution to advance the disciplinary understanding is the potential for this new process to decrease the gap between research and practice.

Teacher self-esteem has been found to impact student learning in a number of non-computing fields. As computing slowly becomes a part of the upper secondary school (high school) curriculum in many countries, instruments designed to measure teachers' programming self-esteem can help inform classroom practice and processes such as teacher professional development needs. This study examines if there are differences in programming self-esteem (using the Bergin Programming Self-Esteem Instrument) between upper secondary school teachers and CS1 students in Ireland. In addition this study provides evidence of validity when using this instrument(originally developed for CS1 students) to measure upper secondary school teacher programming self-esteem. To test for evidence of validity, we compared the results of the programming self-esteem construct given to upper secondary school teachers (n=130) to a recent study of programming self-esteem among CS1 students (n=693). We found evidence of both reliability and validity with teachers that aligns with the evidence found for the CS1 students, demonstrating utility for use with teacher cohorts. Comparing these findings, teachers reported statistically significantly lower programming self-esteem compared to CS1 students. Interestingly CS1 students identifying as male had a statistically significant higher programming self-esteem than those identifying as female. However, we found no statistically significant difference for teacher gender, unlike previous work. Our results indicate that teacher programming self-esteem should be given consideration in the design and implementation of professional development.

Are you interested in improving the quality of K-12 computer science education research? Or maybe you would like to add ideas for additional resources and tools that would save you time while at the same time improving the quality of your own research studies and reports? If so, stop by this Birds of a Feather for a lively discussion on what resources are provided already in the community and to give timely and critical feedback on what features might be added to make your work conducting research studies easier. We will present our near- and long-term plans with the goal of getting your important feedback on the ideas and how we might best prioritize these based on community needs.

In summer 2020, the United States Air Force Junior Reserve Officer Training Corps (JROTC) piloted a Cyber Academy to teach cybersecurity skills and career awareness to high school JROTC cadets. Modeled after the Air Force JROTC Flight Academy, a collaborative effort between the aerospace industry and Air Force to address a national pilot shortage and increase diversity in the field, the Academy lasted 8 weeks and a diverse group of 25 cadets from 12 states participated. The Academy was led by instructors from three institutions, Moraine Valley Community College, Brookdale Community College and Madison Area College. In this experience report, we provide an overview of the curriculum and student learning ecosystem, including the shift from an in-person experience to online due to COVID-19. We present some preliminary findings based on cadets' feedback, grades, and self-efficacy. Despite being an online course that met 3-5 hours per day for 8 weeks, course retention was 96%. Although girls showed much lower cyber threat identification self-efficacy prior to the start of the course than the boys, they reported the same level of self-efficacy as the boys had post-course. We also share lessons learned from the pilot program and future plans for creating a distributed model of the Academy.

As more and more research is conducted in computer science education, particularly as CS content proliferates into primary and secondary education, we are providing to the community a free survey platform specifically designed for conducting research. In this session, we will demonstrate the Research Electronic Data Capture (REDCap) survey platform hosted by CSEdResearch.org, which provides a way for researchers to choose a pre-defined instrument or mix and match a variety of existing scales that meets a researcher's particular study's needs. These instruments have previous evidence of validity and reliability and have been curated for their high quality. By using this platform, researchers can save considerable time (with the ability to select and create a full survey with several existing scales and distribute the survey in less than 10 minutes). In addition to demoing the free-to-use survey system, we will also provide information on how to express formal interest in using REDCap and the training and assistance we provide for researchers and evaluators. (This material is based upon work supported by the U.S. National Science Foundation under Grant Nos. 1757402, 1745199, and 1933671.)

Are you a funding proposal author, a researcher thinking about your data, or someone who is interested in open science? Over the course of three hours we will explore opportunities and challenges associated with preserving and sharing your data, review what the NSF requires of project Data Management Plans and explore tools to help you prepare your data management plan and sustainability strategy. Data sustainability is crucial to contributions to the broader CS education research community and a potential solution to the need for more high-quality datasets available for secondary analyses. There are several challenges associated with maintaining and sharing data, including practical considerations (e.g., sustainable funding, hosting platforms) and ethical concerns (e.g., confidentiality, appropriate contextualization of data in future usage). It is our responsibility to engage with these difficulties and work towards responsible field-wide solutions. This workshop will 1) facilitate participants' discussions of a data sustainability framework, with attention to practical and ethical challenges; 2) introduce participants to tools designed to help enable better data management and data management plans; and 3) allow time for participants to reflect on their current projects? Data Management Plans and brainstorm ways to create processes for facilitating data sharing and sustainability. We invite you to bring plans you may have to the workshop.

This full research paper considers the resources needed to meet the research and evaluation needs of the many efforts to incorporate computing education throughout primary and secondary schools. In order to support these efforts, we developed csedresearch.org, a site designed to serve as a resource center for primary and secondary computing education research. We first considered criteria and recommendations for resource centers previously established by others. We provide a general description of the purpose of the csedresearch.org as well as a description of how we used quantitative and qualitative methods over numerous phases of development (pre-concept/research, concept, alpha, and beta, launch) to ensure that it meets the needs of potential users. We discuss how the current product compares against the general criteria for resource centers, its original intentions and expectations, and how it has fared through the phases of development one normally expects from a digital resource center. As the resource center evolves, we continue to seek feedback and resources to further meet the needs of the community. We also discuss the data that is being collected and could be collected to further benefit the community to define not only what educational practices work best overall, but what works best for particular demographic groups, including underrepresented groups in computing. And finally, we are faced with the challenge for maintaining the information so that remains robust and current.

Efforts to bring computer science to all, particularly in primary and secondary schools, have been unfolding at rapid rates in countries designated as high income economies. Little is known, however, about efforts in middle and even less in low income nations, since the majority of computing education research focuses on high income nations. In this study, we provide context for computing education research in high, middle, and low income countries. We then provide background on K-12 computing education across four countries within one geographic region, South Asia, in which limited research on computing education exists. To gauge what types of enacted curriculum are taught in the classrooms, we modified an existing instrument (MEasuring TeacheR Enacted Curriculum (METRECC)) to meet the culture and current educational climate of these countries. Before trialing the METRECC South Asia instrument, we modified it based on our cultural knowledge of the countries, then acquired feedback from two professionals in South Asia and modified the instrument again based on their input. We then trialed this instrument across two countries. Based on the results and the face validity performed on the instrument, we consider METRECC South Asia to be ready for larger scale usage with recommendations for a broader study. In addition, we consider the role and importance of computing education research in low income countries in order to support the beliefs and values of the CS for All movement.

The sheer number of tools, languages, and environments (TLEs) used in computing education has proliferated in the last few years as more tools are developed to meet new demands of the growing amount of K-12 computing education that has been undertaken. However, there is little formalized language at either the K-12 or post-secondary level that provides for a way to classify these TLEs for discussing research and for classifying in databases.

With the advent of teaching primary and secondary computing education, tools, languages, and environments (TLEs) are important pedagogical support systems for students and teachers. While there are a number of resources available for teaching K-12 students and teachers, there is little synthesis of the data with respect to usage and adoption rates for various TLEs. Using data extracted from 510 articles related to K-12 education, we conducted an analysis using descriptive statistics to determine what TLEs in K-12 are most frequently studied by researchers. We found 193 TLEs being used in research studies and experience reports, then differentiate between these two types of data and between students and teacher professional development. This preliminary research provides a first descriptive analysis of TLEs being used in K-12 space and simultaneously sets the stage for creating a classification system for TLEs based on the literature, including how they are used and what topics (in or outside of computing education) they are used to teach.

Peer review is a mainstay of academic publication - indeed, it is the peer-review process that provides much of the publications' credibility. This working group is examining the ways peer review is used in various computing education venues and will use this examination to articulate community standards for peer review in this discipline.

Until recently, computer science (CS) has been predominantly taught at upper-secondary or tertiary levels. Lately, however, CS curricula have been introduced into school systems from the very first year of school. In this paper, we undertake a participatory research approach, using focus group discussions between a group of experts in the field of evaluation and assessment at the primary level (K-5). The group considered the evaluation and assessment measures they have used, what their current needs are and how the CS education community can move towards meeting those needs. We present the discussion results as a position paper, situated in the context of broader education research. The experts identified three key priorities for the education research community: creating a universal taxonomy of assessment in the primary grades (K-5), creating measurements of student progression and growth over time, and creating culturally relevant evaluations and assessments. Through identifying key priorities, this work provides direction for urgently needed resource development and research directions for K-5 evaluation and assessment.

Computer Science (CS) is a new subject area for many K-12 teachers around the world, requiring new disciplinary knowledge and skills. Teacher social-behavioral factors (e.g. self-esteem) have been found to impact learning and teaching, and a key part of CS curriculum implementation will need to ensure teachers feel confident to deliver CS. However, studies about CS teacher self-esteem are lacking. This paper presents an analysis of publicly available data (n=219) from a pilot study using a Teacher CS Self-Esteem scale. Analysis revealed significant differences, including 1) females reported significantly lower CS self-esteem than males, 2) primary teachers reported lower levels of CS self-esteem than secondary teachers, 3) those with no CS teaching experience reported significantly lower CS self-esteem, 4) teachers with 0-3 years experience had a negative CS self-esteem, but after four years, teachers had a positive CS self-esteem, and 5) teachers who lived further from metropolitan areas and in some countries reported lower CS self-esteem. These initial findings suggest a pressing need for future research to look further into teacher CS self-esteem to inform teacher CS professional development.

The quality of reporting of experimental results in computing education literature has been previously shown to be less than rigorous. In this study, we first examined research standards set forth by four organizations: American Psychology Association (APA), American Educational Research Association (AERA), What Works Clearinghouse (WWC), and the CONsolidated Standards of Reporting Trials (CONSORT). We selected the most important data standards based on their prominence across all four and the most typical study designs in computing education research. We then examined 76 articles designated as quantitative research studies (K-12) published in ten venues (2012-2018) to determine whether the reporting in these articles met these five standards. Findings indicate that only 48% of these articles report effect size and even fewer (11%) report confidence intervals and levels. We found that reported data did not meet the standard that data should be "reported in a way that the reader could construct effect-size estimates and confidence intervals beyond those supplied in the paper". Additionally, authors used existing instruments less than a quarter of the time (24%) and used instruments with evidence of reliability and validity less than half of the time (39%). We conclude with recommendations for those in the K-12 computing education research community to consider when reporting statistical data in future work so that we can increase the level of rigorous reporting in this growing field.

With the advent of computing education in primary and secondary schools, more research will be needed to determine the best way for students to learn how to think computationally and to design and develop software. As a field, computer science education researchers have been predominantly individuals who are steeped in content knowledge, but often have not had formal training in well-established educational research practices. Likewise, many also focus their research on undergraduate students in their own area of teaching. As the need for research into K-12 computing education grows, so does the opportunity for conducting quantitative studies in the field. In this special session, the presenters will present a broad overview of how to conduct and evaluate quantitative computing education research. The presenters will spend approximately 15 minutes on each of the 4 key areas: designing a study, implementing a study and collecting data, analyzing and interpreting results, and reporting on the study. The remainder of the time will be as a question and answer period with the audience. Since there is considerable overlap between computing education research at the primary/secondary and post-secondary levels, those new to research at the post-secondary level may also benefit from learning about form design, implementation, and reporting of research studies. Key takeaways for this session will include a basic understanding of K-12 computing education research from start to finish as well as a list of well-vetted resources to enable new researchers to explore and learn more.

The analysis of data plays an increasingly critical role in computing education research, enabled by more and larger datasets, more powerful analysis techniques and better infrastructure for sharing. This panel brings together four panellists at various stages of work involving the collection and analysis of large datasets in different fields of computing education. The panellists will each discuss the current state of their work, the unique aspects of their data, and how that data fits into the larger landscape of computing education and research. Panellists will be asked to explain how they are employing AI and data mining techniques to learn about learners, the research methods they have used to make this happen, and any significant key findings they have discovered through this processes. The panel will discuss emerging topics, including: going beyond log data, handling global-scale datasets, efficiently collaborating with cross-dataset analysis, and ethical and privacy considerations. After the panelists present (5 minutes each), the moderator will pose follow-up questions and invite the audience to pose additional questions or provide other feedback. Key takeaways will include how data mining and artificial intelligence can contribute to improved insight and learning gains and how the larger computer education community can participate in data collection or analysis.

Developing your computer science education research evaluation instruments from scratch may be no longer necessary thanks to the growing catalog of instruments curated by CSEdResearch.org. This workshop will teach participants how to find, remix, and use existing instruments by delving into the process of taking openly shared resources and repurposing them for your projects. In addition to discussing the importance of using instruments that have been shown to have evidence of reliability and validity, the team from The University of Texas at Austin will discuss how they amended existing surveys and interview protocols to develop tools customized to their needs for their NSF-funded CSforAll Research Practitioner Partnership. Workshop participants will break into groups and be given extensive time to review and revise research instruments. Key takeaways from this workshop will be the steps you need to take to choose an instrument based on your research question and study design, the role that validity and reliability play in instrument design, how to make modifications to an instrument (if needed) to better address your research question, and how to add your instruments to the CSEdResearch.org site.

With the increase in research in the field of computer science education over the last decade, there are datasets with valuable information for researchers, educators and policy makers. Oftentimes in large datasets, it can be difficult to tell what the data represents and this can get more difficult as the datasets grow every year. To help people understand and interpret what is happening in the landscape of computing education research, data visualization can be an important tool. For this study, we used Tableau with CSEdResearch.org's database to show how effective data visualization can be to understand the data. We first used data curated from over 500 articles across 10 publication venues (2012-2018) to analyze the research trends in K-12 computing education in the United states as a sample case. We then expanded the dataset to include 2019 data and created a separate page on the site that presents a portion of this data visually. We then used JavaScript and Tableau "short codes" to provide the capability for users to customize the data represented in the visuals. Data now presented on the site includes a heatmap of the locations of students involved as participants in research studies, the types of research reports provided, and the grade levels, gender, race/ethnicity, and other demographic data. This research provides a glimpse of our techniques and outcomes in working toward the ultimate goal of generating a visual representation of data on the website.

The availability of computer science education in primary and secondary schools in the United States has grown rapidly over the last decade. Computing education research in K-12 has been increasing as well. In this study, we conducted a longitudinal analysis of seven years of data (2012-2018), curated from over 500 articles across 10 publication venues to identify trends in K-12 computing education research such as geographic location and curriculum and concepts taught. The data shows a decrease in the number of studies covering K-12 students receiving computing education even while there is an increase in the number of states adopting and implementing standards. The number of different concepts being researched is increasing, potentially reflecting the growth in what is being taught in the classroom. Demographic data is underreported (e.g., socio-economic status (SES) and disabilities of participants) which could directly limit generalizability of the studies to different learners as well as the ability to replicate and compare studies. We conclude with recommendations for how to better position this work for others trying to use the results to guide their efforts in creating standards or adopting techniques into their classrooms.

Open science in computing education has been focused primarily on the data collected by automated learning systems such as those developed in intelligent tutoring systems and rote drill exercises. There is another aspect of data collection that is being continually conducted throughout K12 and post-secondary computing education through surveys, summative assessments, interviews, and other methods to measure cognitive (e.g., algorithms, data structures, pointers) and noncognitive (e.g., self-efficacy, grit, attitude) factors. As a new field, we have the unique advantage of being able to build and share practical and comparable datasets in K-12 computing education that meets some of the new guidelines and best practices being put forth by the National Science Foundation and Department of Education. This short paper describes the data being collected that is now available as part of CSEdResearch.org, what is needed to add the capability to collect and compare additional data through collaborative open science practices, and a path towards meeting those needs. This work furthers Open Science by defining how to access the data that already exists in CSEdResearch.org as well as what is needed to create additional tools for researchers and evaluators to enter K-12 computing education data directly on the site. By creating the infrastructure for shareable data that meets current and evolving open source guidelines, the community can start to use this data to develop best practices from empirical evidence.

In an effort to evaluate computer science education using more modern, automated data science techniques, we consider Hattie's work in Visible Learning then define a comprehensive framework to provide the capability to automatically generate a quantitative meta-analysis using predefined moderators (e.g., age, grade, etc.) with data derived from multiple individual research studies. To define the initial criteria, we developed a list of critical questions that the framework must address, including what moderators are most important to include, how to address homogeneity across various studies, how to define categories of influencing factors, and how to compute summary effect size. This initial framework describes how the meta-analysis is derived from effect sizes that are calculated based on each mean and standard deviation reported in experimental and quasi-experimental studies. Since the goal of this foundational research is to create an auto-generated meta-analysis tool, we define a basic user experience that would allow users to select moderators and predefined levels of heterogeneity (such as "include only random control group studies" or "include studies reported in journal articles") for inclusion in the meta-analysis. We conducted a feasibility study of the framework using data (number of participants, mean, standard deviation) collected from 21 data samples curated from eight computer science education articles with a primary and secondary focus across ten venues (2012-2018). We consider what we learned conducting the study, including the need for full system transparency, issues related to data integrity, and issues related to defining and selecting appropriate formulas for differing sets of data.

There has been a growing interest and increase in work shared about national K-12 Computer Science Education (CSED) curriculum and implementation efforts around the world. Much of this work focuses on curriculum analysis, country reports, experience reports and case studies. The K-12 CSED community would benefit from an international strategic effort to compare, contrast and monitor K-12 CSED over time, across multiple countries and regions, to understand pedagogy, practice, resources and experiences from the perspective of teachers working in classrooms. Furthermore, there is a need for validated and robust instruments that can support comparable investigations into the current state of K-12 CSED in schools around the world. Through a collaborative effort, this Working Group will develop a validated teacher survey instrument and collect data about CSED implementation and practice in K-12 classrooms. The authors will pilot the survey with K-12 teacher cohorts and analyse, compare and contrast survey findings across countries.

No abstract available.

In this Tips, Techniques, and Courseware talk, we will provide an overview of csedresearch.org, a site designed to provide resources for primary and secondary computer science (CS) education researchers. This resource center has three primary functions: 1) to provide a quick and easy way to search and access manually-curated data from over 500 articles from ten targeted venues (currently 2012-2018), 2) to provide a centralized location for evaluation instruments, many of which are focused on computing, and 3) to provide resources for computer science education research (checklists for studies, how to design a study, how to write a research question, etc.). Users can search for articles by filtering at a granular level on various curriculum and activity components, including student demographics, instructor demographics, and program components. Users can also search for evaluation instruments on criteria such as type, year published, constructs measured in the instrument, and whether the instrument has been validated or tested for reliability. We will provide a brief summary of the rationale for the site, the current state of the site, and how educators and researchers are using the site to date. We will also discuss future plans for the site and enable the audience to provide feedback that may help us shape the site to better meet the needs of the community.

In this Tips, Techniques, and Courseware presentation, we will provide an overview of If Memory Serves, a game designed to complement the instruction of pointers in computer science courses. The game was first designed during a working group in ITiCSE 2017 as a tool to enable deeper understanding of pointers due to the difficulties students often face when learning about them. Over the last two years, the game has continued to evolve and has moved from a concept of the game to near-alpha. During this talk, we will demonstrate the game, provide insight into why it was developed, and discuss how it can be used to teach pointers. We will also briefly discuss our concept behind this open-source game and invite feedback from the audience as well as invite others to remix, test, and engage in research on testing the game's effectiveness.

As computing education research continues to grow and mature as a field, it becomes more important to focus on the quality and rigor of our research studies. One important aspect of any research study is its formal evaluation. Using standardized and validated instruments relevant to computer science education to perform evaluations can increase the quality of the study and the value of its results. However, researchers often create their own instruments rather than using existing ones, perhaps due to their lack of knowledge of the value of using an existing instrument or due to the challenge of finding such instruments. Through a review of relevant computing education literature, this paper presents a listing of 47 evaluation instruments specifically designed for measuring programs or constructs related to computing that can influence student achievement and learning. Analysis of purpose, target audience, reliability, and validity of the instruments is also presented. The paper ends with a call for the community to begin to make more regular use of validated instruments in their studies when possible and to develop and validate additional instruments in areas where few exist.

A growing body of evidence indicates that there is a deep effect of noncognitive factors on academic achievement and learning. In this study, we analyzed a set of 31 evaluation instruments designed to measure noncognitive constructs (e.g., self-efficacy, confidence, motivation) within computing education. Using the Lee and Shute framework, we assigned each of the 115 unique constructs found in the instruments into one of the four components (Student Engagement, Learning Strategies, School Climate, Social-familial Influences) and their subcomponents to determine which constructs are most frequently measured. We found that the majority of constructs were designed to measure Student Engagement (Affect and Cognition) and School Climate (Teacher Variables). Constructs measuring Learning Strategies and Social-Familial Influences (e.g., homework strategies, peer influences) occur the least. This study may enable further discussions of what noncognitive factors are/are not currently being measured within the computing education community.

This Research Full Paper describes the early research conducted to design a searchable repository of peer-reviewed research related to pre-college computing activities. This repository is part of a larger project to enable the computer science education community to gather and analyze data related to the effectiveness of these activities. To ensure that the repository met the needs of the community, we convened a virtual focus group of experienced and expert researchers and educators to discuss the repository's value, what it should contain, and how it should be presented. This paper presents 1) an analysis of these discussions, which shows that participants were equally interested in the repository's content and quality, 2) an initial list of variables that can affect the outcomes of these activities, and 3) an initial set of questions researchers should ask when authoring computer science education research involving precollege computing activities. We also consider these results in light of the larger challenge raised by others of how to improve quality research in computing education.

Over the last few years, a number of repositories of information relevant to the computing education community have come online, each with different content and purpose. In this special session, we present an overview of these repositories and the content that each provides. Demonstrations of the functionality of the repositories will be shown and attendees are encouraged to come with their questions and suggestions for improvement if they are currently users of the repositories.

With the growth of computing education research in the last decade, we have found a call for a strengthening of empiricism within the computing education research community. Computer science education researchers are being asked to focus not only the innovation that the research creates or the question it answers, but also on validating the claims we made about the work. In this session, we will explore the relationship between evaluation and computing education research and why it is so vital to the success of the many computing education initiatives underway. It will also help computing faculty engaged in computer science education research understand why it is essential to integrate evaluation and validation from the very first conceptual stages of their intervention programs.

This paper provides a detailed examination of pre-college computing activities as reported in three Association of Computing Machinery (ACM) venues (2012-2016). Ninety-two articles describing informal learning activities were reviewed for 24 program elements (i.e., activity components, and student/instructor demographics). These 24 program elements were defined and shaped by a virtual focus group study and the articles themselves. Results indicate that the majority of authors adequately report age/grade levels of participants, number of participants, the type of activity, when the activity was offered, the tools/languages used in the activity, and whether the activity was required or elective. However, there is a deficiency in reporting many other important and foundational program elements, including contact hours of activity participants, clear learning objectives, the prior experience of participants (students and instructors), and many more. In conjunction with previous work, this paper provides recommendations to reduce these deficiencies. The Recommendations for Reporting Pre-College Computing Activities (Version 1.0) are presented to help researchers improve the quality of papers, set a standard of necessary data needed to replicate studies, and provide a basis for comparing activities and activity outcomes across multiple studies and experiences.

Educators have long used digital games as platforms for teaching. Games tend to have several qualities that aren't typically found in homework: they often situate problems within a compelling alternate reality that unfolds through intriguing narrative, they often draw more upon a player's intrinsic motivations than extrinsic ones, they can facilitate deliberate low intensity practice, and they often emphasize a spirit of play instead of work.

Europe, Australia, and North America face two similar challenges with respect to computing--there have not been enough students matriculating to keep up with demand and the lack of diversity remains an issue. To address these challenges, private and public resources have been allocated to educate primary and secondary students in computing. Previous meta-studies on these often segregated outreach efforts within the United States indicate that research on their impact remains spotty, short-term, and inconsistent, leaving a gap in the ability to evaluate their long-term impact. Building upon previous research focused in the U.S., this study examines similarities and differences in the results of 17 formal, peer-reviewed computing education research journals and conferences across Australia, Europe, and North America during 2009-2015. Results indicate that a lacuna exists in international research, paralleling results of the more narrowly focused study of U.S. venues. The paper further defines the major issues researchers face in conducting assessment studies for outreach and recommendations for addressing this gap.

There is a critical need to increase the number of skilled technology workers in part due to the supply of workers in these fields not yet keeping up with demand. In an effort to increase the interest of students in studying within these fields, many commercial, governmental, and non-for-profit educational groups have sponsored numerous activities aimed to expose students to computing prior to college. With the advent of CS for All, there is further need to research these programs and evaluate their effectiveness. This session will gather researchers and practitioners interested in researching the impact that pre-college computing activities have on their participants. Participants will learn about a new initiative underway to make the job of collecting and tracking data easier. To be useful for the broader community, this NSF-funded IUSE initiative requires input from the community it wishes to serve. Participants will have the opportunity to provide valuable input on what their needs are for tracking such activities and what tools may be helpful for them, including methods for data collection to produce meaningful data that can be compared to data provided by other researchers and practitioners. The focus of this discussion will be the long-term impact of these activities; however, we will discuss data collection techniques researchers have used in the past to gauge short-term impact as well.

In the past six years, dozens of conference papers and journal articles have been presented in Association of Computing Machinery (ACM) and Institute of Electrical and Electronics Engineers (IEEE) educational forums concerning computing outreach activities. Nearly half of these (47.5%) appeared in SIGCSE venues. In this study, we used the free-form question "What type of data has been collected in formal, peer-reviewed research that has been conducted on computing outreach activities in recent years"? as a basis for a systematic literature review in these venues from 2009-2015. During the analysis of the articles, it was discovered that a majority of efforts focused on middle school and high school students, a majority of the reported events took place in the United States, and almost half had a goal of increasing gender diversity in computing. This paper summarizes the information about the studies, including their data collection techniques and the data that was collected. We also present a list of recommended practices for data collection, methodologies, and reporting for educational researchers engaged in these activities in an effort to provide comparative data and allow us as a community to more scientifically understand the impact that these activities are having on the participants.

A lack of diversity in the computing field has existed for several decades, and although female participation in computing remains low, outreach programs attempting to address the situation are now quite numerous. To begin to understand whether or not these past activities have had long-term impact, we conducted a systematic literature review. Upon discovering that longitudinal studies were lacking, we investigated whether undergraduate students believed that their participation in computing activities prior to college contributed to their decision to major in a computing field. From the 770 participants in the study, we discovered that approximately 20% of males and 24% of females who were required to participate in computing activities chose a computing or related major, but that males perceived that the activity had a greater affect on their decision (20%) than females (6.9%). Females who participated in an outreach activity were more likely to major in computing. Compared with females who chose to major in computing, females who did not were less likely to indicate that the majority of students participating in activities were boys and that they were a welcome part of the groups. Results also showed that female participants who do not ultimately major in computing have a much stronger negative perception of the outreach activities than male participants who also chose a non-computing major. Although many computing outreach activities are designed to diversify computing, it may be the case that, overall, boys receive these activities more favorably than girls, although requiring participation yields approximately the same net positive impact.

Over the last decade, there has been a concerted effort to bring more diverse voices to the technology field, with much of this being done through outreach activities to girls and boys. Unfortunately, data demonstrating the long-term impact of outreach activities remains rare. To contribute to knowledge on the longitudinal effect of outreach programs, we used a quantitative methodology that followed a descriptive design approach to explore the impact of participation in outreach activities on the choice of undergraduate major. Of those surveyed, 45.3% of the 770 respondents recalled participating in these activities. The results indicate that these activities had a more positive impact on Asians and more negative impact on Hispanics. Blacks/African Americans were more likely to voluntarily participate in outreach activities than Hispanics, and whites were more likely to feel that they were a welcome part of the group than non-whites. The results also may indicate that when outreach programs are available in earlier grades, they are not reaching non-white participants to the same extent as white participants.

One of the goals of using robots in introductory programming courses is to increase motivation among learners. There have been several types of robots that have been used extensively in the classroom to teach a variety of computer science concepts. A more recently introduced robot designed to teach programming to novice students is the Institute for Personal Robots in Education (IPRE) robot. The author chose to use this robot and study its motivational effects on non-computer science students in a CS0 course. The purpose of this study was to determine whether using the IPRE robots motivates students to learn programming in a CS0 course. After considering various motivational theories and instruments designed to measure motivation, the author used Keller’s Instructional Materials Motivation Survey to measure four components of motivation: attention, relevance, confidence, and satisfaction. Additional items were added to the survey, including a set of open-ended questions. The results of this study indicate that the use of these robots had a positive influence on participants’ attitudes towards learning to program in a CS0 course, but little or no effect on relevance, confidence, or satisfaction. Results also indicate that although gender and students interests may affect individual components of motivation, gender, technical self-perception, and interest in software development have no bearing on the overall motivational levels of students.

Digital games are marketed, mass-produced, and consumed by an increasing number of people and the game industry is only expected to grow. In response, postsecondary institutions in the UK and the U.S. have started to create game degree programs. Though curriculum theorists provide insight into the process of creating a new program, no formal research contextualizes curriculum planning for game degree programs. The purpose of this research was to explore these processes when planning undergraduate game degree programs. The research methodology included an explanatory mixed-methods approach, using a quantitative survey of participants in the UK and the U.S., followed by interviews with several participants selected on the basis of their institution’s demographics. Results indicate that five external factors influence the development of game programs (government, industry, other universities, society, and trade associations) and eight internal factors influence curriculum planning (facilities, faculty, institution, interdisciplinary collaboration, learners, learning time and space, originating department, and backgrounds of the planners). Results also indicate that while some differences exist in the game degree programs across countries, the vast majority of curriculum planning processes and influencing factors are the same. The study concludes with a set of recommendations for educators, trade associations, and the games industry to improve game degree programs.

Due to the recent creation of game degree programs at post-secondary institutions, peer-reviewed literature on the curriculum planning process for game degrees at post-secondary institutions pales in comparison to the literature available for more established fields of computer science. At Bradley University, departments across colleges have worked collaboratively to create two cross-disciplinary game minors. The minors have been carefully crafted to nurture the growth of both media designers and software developers while simultaneously providing experiences for the students to experience multi-disciplinary teamwork. This paper details the creation of these two innovative game minors with emphasis on three aspects of the curriculum planning process: 1) their interdependencies, 2) their structure for supporting both Design and software development students, and 3) their reliance on the International Game Developer Association's curriculum framework. In addition, the author provides a summary of issues and concerns that arose during the curriculum planning process.

When developing a game curriculum, one of several key areas to consider is the type of skills needed by the game industry. The purpose of this quantitative survey research is to compare the hiring needs of industry for recent college graduates seeking game developer positions against game development curriculum currently available at post-secondary institutions. One survey was given to industry participants and a similar survey was given to academic participants. Four major categories, abilities, technical skills, supporting knowledge areas, and contextual fluency, each had specific subcategories that were rated by both industry and academia. A t-test of independent means was then used to analyze to determine if there is an expectation gap between the game industry needs and academic program curriculum. This paper details the results of the surveys and provides a limited discussion on how these results might impact game developer curriculum.

One of the more intriguing areas in game-based learning is the phenomenon of gaming and its impact and potential in education. As most dissertation work evolves, my topic area is still broad and is focused on the effectiveness of learning in games designed for high school science students. Though much previously performed research indicates that games increase engagement of students and that students view this method of learning favorably, current research indicates that hypothesis-based games and games that are incorporated as part of the teacher's curriculum may separately have a greater impact on student learning. The proposed research will examine the impact these two variables, hypothesis-based games and games that are incorporated into the curriculum, have on learning. Specifically, the research method will examine the differences in the effectiveness of learning without games, learning with games that are hypothesis-based and that are not incorporated into the instructional curriculum, learning with games that are not hypothesis-based that are incorporated into the instructional curriculum, and learning with games that are hypothesis-based and incorporated into the learning curriculum. Control and treatment groups will be used in this experimental study.

Game development programs are being added to computer science departments as either a track, minor, or major in post-secondary institutions across the United States. These programs are being developed with little published quantitative or qualitative research on what such programs should entail. The quantitative research in this pilot study defines qualifications sought when hiring game developers for positions in industry. Using cross-sectional data, qualifications from job advertisements were coded, categorized, and then subcategorized and weighted totals were calculated based on skills being either required or desired. Weighted totals in each subcategory were compared and ranked. The top 10 qualifications are provided, along with a breakdown of rankings of all subcategories within each category. Subcategories of Languages and Tools/Environments are also discussed briefly to highlight key qualifications in each.