In the spring of 2022, a formerly vibrant summer reading program had become moribund due to retirements and staff changes; roughly 1600 first year students were about to miss out on a longstanding and successful tradition. In response, a small group of faculty sought a way to link first-year courses between disciplines in order to boost student engagement. This group latched upon a fortuitous circumstance: the 101st anniversary of Karel Capek's play R. U.R., which gave the world the term “robot.” Thus was born Robot 101, an integrative experience connecting instructional content between courses and with a wide range of academic and artistic events outside the classroom, all centered around the multifaceted theme of “robot.” This paper details how a common theme can inform and enliven first-semester courses in engineering, composition, and computer science, as well as engage the greater university community. Our primary objective in establishing these overt connections between courses and other activities was to give students the opportunity to form their own covert connections, thereby deepening their appreciation of the interdisciplinary nature of big ideas in engineering, technology, and society. The program also provided opportunities for more advanced students to participate and make their own interdisciplinary connections. This work provides initial data and reflections on the effect of this program on student engagement and connectedness in first semester courses. We include recommendations for a scalable and sustainable program that continues thematic integration on an ongoing basis.

Analogy is a frequently leveraged pedagogical tool used across many disciplines, with computing being no exception. Computing education researchers, however, have raised concerns regarding the limitations of analogy. One obvious concern is the relevance of any given analogy to learners. Designing relevant analogies can greatly increase student engagement with the problem space by centering examples on their lived experiences. Relevant analogies can also facilitate learners in building appropriate connections as they explore novel concepts.

A concurrent computing course is filled with challenges for upper-level programming students. Understanding concurrency provides deeper insight into many modern computing and programming language behaviors, but the subject matter can be difficult even for relatively proficient students. It can be a challenge to help students navigate and understand these unfamiliar topics. While there is a difference in general programming familiarity, teaching this novel material is not unlike some challenges faced when engaging introductory students with first programming concepts.

Concurrent programming can be a rewarding but challenging topic for computing students. Comprehending concurrency can help students gain a better understanding of the computer as a machine, and how processes within modern machines execute and interact. Knowledge of concurrency is important to develop secure and robust multithreaded programs. However, understanding this topic at a machine and syntactic level can be difficult for students due to its novelty and complexity. Several topics in concurrent computing can initially be explored at a high-level using real-world examples and analogies to facilitate comprehension. This paper explores perspectives provided by university students in a concurrent programming course on the use of analogy to facilitate learning about concurrent topics. Through this paper, we draw attention to analogies used in course examples and assignment prompts, while turning attention to how students interpret and reason about and with these. We also explore new analogies these students crafted while reasoning about the problem space. This exploration suggests that while these students may draw attention to different aspects (in different ways) of an analogy's design, they generally approach similar conclusions in their reasoning process provided the core relational design remains intact. Students also applied prior analogies from lecture and past assignments, actively reasoning during problem solving with these known examples. There is also some evidence of analogy mixing and swapping, suggesting malleability in analogy use while problem solving. Together, this exploration contributes to understanding student problem solving, reasoning behaviors, and perspectives while using analogy within concurrent computing courses.

Within computer science education research, analogy work has been relatively unexplored and in some cases, even discouraged. For a learning and reasoning tool that is so widely used in our discipline - from instructors and peer groups to the interfaces we encourage students to program on - it is beyond time to address the perception of analogy in our field.

This position paper discusses the need for greater inclusion of context in papers describing computer science education research. This inspiration arose from our efforts to compare our experiences with pair programming in an introductory computer science course with experiences described in the literature. We quickly observed that the behaviors associated with the term "pair programming" and the contexts can differ greatly between universities and yet the phrase pair programming is often used with no further explanation.

Climate change is the defining environmental challenge now facing our planet. Babies born today will be 22 when global warming reaches 1.5 C, according to the latest IPCC report and forecasts. What will life be like in 2040? How do we as educators respond today, to the challenges that lie ahead for the next generation?

This Innovative Practice Work in Progress focuses on encouraging the persistence of computing majors. Research has shown that one factor in whether or not a student persists in a computing major is a sense of belonging. We are using Myers-Briggs personality types to help students see that even if they feel they are currently in a minority, others who are similar to them are successfully enjoying a computing career. It is our hope that our discussion of Myers-Briggs personality types also facilitates students' understanding of the value of diversity in a computing environment.

A broad review of research on the teaching and learning of programming was conducted by Robins et al. in 2003. Since this work there have been several reviews of research concerned with the teaching and learning of programming, in particular introductory programming. However, these reviews have focused on highly specific aspects, such as student misconceptions, teaching approaches, program comprehension, potentially seminal papers, research methods applied, automated feedback for exercises, competency-enhancing games, and program visualisation. While these aspects encompass a wide range of issues, they do not cover the full scope of research into novice programming. Some notable areas that have not been reviewed are assessment, academic integrity, and novice student attitudes to programming. There does not appear to have been a comprehensive review of research into introductory programming since that of Robins et al. It is therefore timely to conduct and present such a review in order to gain an understanding of the research focuses, to highlight advances in knowledge since 2003, and to indicate possible future directions for research. The working group will conduct a systematic literature review based on the guidelines proposed by Kitchenham et al. This research project is well suited to an ITiCSE working group as the synthesis and discussion of the literature will benefit from input from a variety of researchers drawn from different backgrounds and countries.

Multiple studies have shown that when novice and experienced programmers are enrolled in the same introductory programming course, the novice programmers are negatively impacted. We have two entry points into our course sequence for majors. One course is intended for students with little or no programming experience, while the alternate course is intended for students who have had previous programming experience. In 2015 we discovered that many students with programming experience were enrolling in the course for novice programmers. A change in our placement strategy in 2016 resulted in a greater portion of the students with programming experience actually enrolled in the course intended for students with programming experience. Last year we reported on the impact this change had on the courses and the students enrolled in these introductory courses. Although student performance improved only slightly, many fewer students with little or no previous programming experience reported that their first programming course was unreasonably difficult in 2016. In this paper we examine how this change in placement strategy and resulting changes in the courses is impacting student persistence in the major. Initial indications are that a greater percentage of students with little or no previous programming experience are persisting in their computing major when these students begin in an introductory course that does not also include students who have substantial programming experience.

The need for K-12 students to engage in Computer Science has been acknowledged in the White House call for "Computer Science for All" and supported through a variety of institutions. Implicit in many initiatives, and explicit in Google's CS4HS initiative, is the notion of a "Community of Practice" involving K-12 teachers. Communities of Practice are mutually supportive groups to assist newcomers as they find their way in a new endeavor. Teachers can support one another at multiple levels: technical, pedagogical, political, and emotional. Maintaining a Community of Practice for CS teachers, however, can be challenging. Demands on teacher time, lack of institutional buy-in, physical isolation, and lack of appropriate peer institutions are some confounding factors. A true community of practice requires maintenance: ways to identify newcomers or other participants in need, and ways to identify and share the resources that can help others. In this BoF, educators who are working to expand CS within K-12 education will discuss the challenges in the Community of Practice approach and share proven ways of addressing them.

Studies have shown that novice programmers face unnecessary obstacles when they are enrolled in an introductory course alongside students with previous programming experience. Thus a recommended best practice is to have separate courses or separate sections for novice and experienced students in introductory programming courses. At Michigan Tech we have two starting points for our introductory sequence with one aimed at novice programmers and a second aimed at students with some programming experience. We, therefore, assumed that the curriculum was in alignment with this best practice. A survey of our incoming students indicated that students were not enrolling in the courses consistent with our expectations. By changing the timing and means of offering an assessment to determine student placement in the introductory sequence, we were able to substantially impact the make-up of our introductory courses. The change did have the desired positive impact on students in the course for novice programmers. In this paper, we will also discuss some of the other issues we uncovered with this change.

In November 2014, Michigan Technological University's departments of computer science (CS) and electrical and computer engineering (ECE) were selected to participate in NCWIT's Extension Services for Undergraduate Programs (ES-UP). ES-UP, supported by NSF and Google, is designed to help departments develop strategies to recruit and retain women in computing and engineering majors. Both departments have enrolled a low number of women in their programs and have had lower retention rates than other departments on campus. As part of the ES-UP initiatives, we surveyed our first-year students in Fall 2015 and followed up with a second survey in January 2016. The goal of the initial survey was to learn what attracted students to their major while the second focused on their experiences during their first semester. Examination of the students across the four majors in the two departments in separate colleges provides a unique perspective on students' attraction to and persistence in computing-related majors.

There are many challenges in changing the diversity in engineering. In the Catalyzing Collaborative Conversation, we explored ways to change the diversity climate through outreach, recruitment, and retention methods to help students succeed and achieve the goal of becoming an engineer.

Student persistence in computing majors is one of the keys to providing the talent needed to fill the projected job openings in the computing professions. A range of factors can affect a student's decision to remain in a computing major or change to another major. In this paper we describe an assignment that we use in a course for first semester computing majors. The assignment is based on students interacting with alumni on an individual basis. The nature of the assignment addresses a number of the factors that have been shown to influence students' persistence and may result in an individual student getting the specific intervention that he or she needs.

Retention has traditionally been an issue in many introductory computing courses and major degree programs. In Fall 2013 we saw an anomaly with particularly high persistence and success rates among students in our majors-only explorations course. A close examination revealed a similarly higher than usual success and persistence rate by our majors in the first programing course they were taking simultaneously with the explorations course. These successes were presumably related to the better than usual retention of first year students within our Department from the first to second semester. This paper presents the curriculum changes and analyses the change in student performance. The relationship between our curriculum changes and what other researchers have observed are examined in an effort to identify the reasons for the increased student persistence. The potential for either a positive or negative interplay between our two courses is also discussed. Insights from these findings that may be of use to others are presented.

This HCI course incorporated unit testing as a quality improvement initiative with an Experiential Learning Model. The focus of the research was on observation and conceptualization---students should be able to associate the benefits of usability and unit testing and apply them to more general situations. Based on our survey results and student interviews, the most difficult challenge incorporating unit testing in an experiential course was ensuring students overcome their negative bias to discover the benefits of functional testing. We recommend emphasizing the concrete benefits of unit tests and ensuring that all students fully participate in the testing experience.

The Fulbright Scholar Program is the flagship academic exchange program of the U.S. Department of State; approximately 1,100 American scholars travel worldwide annually to lecture and conduct research. The program is open to all U.S. citizens with university teaching experience and a Ph.D. or equivalent professional/terminal degree. Opportunities for Computer Science educators to win Fulbright scholarships are many. The goal of this panel is to inform the community of computer science educators about the Fulbright program, including the application process, and to answer questions about the program. After an introduction to the program at large, the panelists will each give a 10-15 minute overview of their personal experience as a Fulbright scholar in 2011-2012, leaving ample time for questions from educators considering applying for a Fulbright scholarship. The panelists will offer diverse perspectives based on their experiences in India, Zambia, and Siberia.

We examine the functional cohesion of procedures using a data slice abstraction. Our analysis identifies the data tokens that lie on more than one slice as the "glue" that binds separate components together. Cohesion is measured in terms of the relative number of glue tokens, tokens that lie on more than one data slice, and super-glue tokens, tokens that lie on all data slices in a procedure, and the adhesiveness of the tokens. The intuition and measurement scale factors are demonstrated through a set of abstract transformations.>

Program slices are used to model module cohesion. For the authors purposes, a slice is a projection of program text that includes only the data tokens relevant to one output. The authors define six cohesion metrics in terms of these slices, and evaluate the effects of classes of module changes on these metrics. They find that the effects on cohesion metrics are notably more predictable when the changes result from adding code rather than from moving code.>

High module cohesion is often suggested as a desirable property of program modularity.The subjective nature of the definition of cohesion, however, can make it difficult to use in practice.In this paper, we examine the relationship between the data flow in a module and its level of cohesion using aprocessing element frow graph (PFG).Based on these PFG's, we regroup the original seven levels of cohesion into four classifications.Slice projiles are then defined by generating slices for all output variables of a module.A relationship is then shown between these slice profiles and the PFG used to indicate levels of cohesion.It is suggested that these slice profiles can be used to determine more easily the cohesiveness of a module.