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Two studies investigated change in computer science (CS) students’ implicit intelligence beliefs. Across both studies, we found that the strength of incremental and entity beliefs changed across time. In Study 1, we found that incremental beliefs decreased and entity beliefs increased across the semester. Change in implicit intelligence beliefs was similar for students taking introductory and upper-division courses. In Study 2, growth curve analysis revealed a small linear change in incremental beliefs across time but no change in entity beliefs—these trends were similar for students enrolled in introductory and upper-division CS courses. Across both studies, change in implicit intelligence beliefs was not associated with academic achievement in CS. Findings provide preliminary evidence that shifts in implicit intelligence beliefs occur as students progress through the CS curriculum. Finally, findings support that mindset interventions may be more effective if delivered at the beginning of the semester before shifts in beliefs occur.

Contribution: This article presents a synthesis of the findings and implications from the IC2Think program of research in undergraduate computer science (CS) courses examining student motivation and self-regulated learning (SRL). These studies illuminate both the difficulty and potential for motivating CS students, as well as the uniqueness of CS as a context for studying undergraduate motivation. Background: Computing disciplines are increasingly important in preparing the future workforce. It is imperative that CS educators understand how to motivate students and enhance student outcomes. Synthesizing findings across multiple studies allows for the emergence of new insights into student motivation and SRL. Research Questions: Which aspects of students’ motivation and SRL are predictive of achievement and retention in CS and how can findings inform CS education? Methodology: The primary methodology is a comprehensive review of seven years of research on undergraduate CS education. Studies use a variety of analysis techniques, examine a range of constructs, and include multiple introductory and advanced CS courses. Studies of relationships between variables and change over time were conducted. Findings: The present synthesis of studies on motivation and SRL highlights the complex, counter-intuitive, and positive aspects of student motivation in CS.

Objective: To test if precollege drinking data gathered during an online brief intervention are associated with problems and could inform screening for campus alcohol prevention efforts. Participan...

The theme of IEEE ICCI*CC'16 on Cognitive Informatics (CI) and Cognitive Computing (CC) was on cognitive computers, big data cognition, and machine learning. CI and CC are a contemporary field not only for basic studies on the brain, computational intelligence theories, and denotational mathematics, but also for engineering applications in cognitive systems towards deep learning, deep thinking, and deep reasoning. This paper reports a set of position statements presented in the plenary panel (Part I) in IEEE ICCI*CC'16 at Stanford University. The summary is contributed by invited panelists who are part of the world's renowned scholars in the transdisciplinary field of CI and CC.

To determine whether completing a pre-enrollment Web-based alcohol brief motivational intervention (BMI) increased student retention and reduced student alcohol-related violations.Fall 2011 (3,364) and Fall 2012 (3,111) entering cohorts of all first-year students at a midwestern state university.Students completing the brief intervention (BI) were compared to students not completing the BI. Retention was tracked for four years for the 2011 cohort and three years for the 2012 cohort. Campus and community alcohol violations were tracked for two academic years following enrollment. Kaplan-Meier survival analysis and Cox regression were used to test retention survival. Logistic regression was used to test campus and community violations.Students in both cohorts who completed the BI had significantly higher retention and significantly fewer alcohol-related violations than noncompleters.Population-level Web-based BIs help prevent student dropout and decrease alcohol-related violations, with impacts extending multiple years. Web-based BI is an efficacious population-level prevention tool.

Contribution: This paper provides evidence that computational creativity exercises (CCEs) can increase engineering students’ learning in introductory computer science (CS1) courses. Its main contribution is its more rigorous treatment/control group research design that allows testing for causal influences of CCEs on student learning and performance. Background: Computer science (CS) courses are critical foundational courses for engineering students. CCEs that merge computational and creative thinking have been shown to increase achievement and learning of engineering and nonengineering students in CS1 courses, but previous research has used quasi- and non-experimental designs. Intended Outcomes: CCEs are intended to improve students’ learning of CS1 content and problem-solving ability by fostering computational creativity. Application Design: CCEs can improve student learning and can be used to supplement other evidence-based instructional practices. Findings: Propensity score matching was used to create equivalent treatment and control groups; results show that students in the CCE implementation section had higher scores on a CS knowledge test than students in the control section, but not higher self-efficacy for their CS knowledge. Focus group and open-ended survey questions indicated that students had mixed reactions to the CCEs, with about half the students seeing them as improving their learning, understanding, and ability to apply CS in their engineering field. Responses also reinforced the importance of fully incorporating CCEs in courses and aligning them with course topics.

This research investigated the relationships among undergraduate computer science students’ computer-science-related career aspirations, perceived instrumentality (PI) for computer science courses, and achievement in those courses. Specifically, the two studies examined (a) change in PI and career aspirations during a single semester, (b) the relationship between change in career aspirations and change in PI, and (c) the influence of career aspirations, PI, and change in career aspirations and PI on achievement in computer science courses. Findings from both studies revealed that students experienced a decrease in endogenous PI and career aspirations and an increase in exogenous PI during the semester. Study 1 showed that non-computer science majors experienced greater shifts in PI and career aspirations than computer science majors. Study 2 showed that the change in PI happened in parallel and was curvilinear, with more change happening in the first half of the semester than the second half. Both studies also showed that computer-science-related career aspirations were associated with PI, and that aspirations and PI had a stronger relationship with scores on a computer science knowledge test than with course grades. Implications and directions for future research are discussed.

China’s National Physical Fitness and Health Surveillance(NPFHS)survey revealed high levels of sedentary behavior among primary school-aged children. Sedentary behavior is linked to both short-term and long-term physical and mental health conditions. A comprehensive school health education program was designed and its effectiveness to raise physical activity levels in Grade 4 primary school children was evaluated. Twelve schools(6 of program, 6 of control)from six cities in two economically different provinces were selected. Students at program schools received physical activity instruction both in and out of school. Control schools carried on with their usual level of physical activity for students, as required by national educational standards. Program effectiveness was assessed by comparing students’ physical activity behaviors at pre- and post-program, and by comparing students’ physical activity scores at program schools with students’ scores at control schools. The pre-program survey of students’ behaviors was done at the end of Grade 3, and the post-program survey was done at the end of Grade 4. Multi-level modeling was used to evaluate program effectiveness to allow for missing data. Results from 4472 students showed at pre-program there was no difference in control and program schools’ student physical activity scores. At post-program students in program schools did significantly more physical activity compared to students in control schools. Students in program schools were more physically active after the comprehensive school health education program. A school-based comprehensive health education program would effectively increase children’s physical activity level in China. There is a potential to reduce sedentary behavior among children by implementing school programs that are environmental in nature; that is, activities involve not only the students, but also the school administration, teachers, parents, and community members.

This study examined peer group influence on university student drinking in China and the indirect effects of peer pressure and self-efficacy for alcohol self-regulation. A total of 951 undergraduate university students (first, second and third year) from a university in central China completed questionnaires asking about perceived peer pressures, self-efficacy for alcohol self-regulation, and drinking frequency. Analysis of their answers showed that the drinking frequency among physical education (PE) students was higher than among the comparison group (History students). The PE students perceived greater peer pressure, and had lower self-efficacy for alcohol self-regulation, both of which contributed directly to drinking frequency. Path analysis indicated indirect effects of peer pressure and self-efficacy for alcohol self-regulation on the association between peer group membership and drinking frequency. This suggested that skills training to increase self-efficacy for alcohol self-regulation in culturally-specific settings have the potential to both directly and indirectly lower drinking rates in peer groups with high peer pressure and higher than normal drinking.

Computational thinking and creative thinking are valuable tools both within and outside of computer science (CS). The goal of the project discussed here is to increase students’ achievement in CS courses through a series of computational creativity exercises (CCEs). In this paper, the framework of CCEs is described, and the results of two separate studies on their impact on student achievement are presented. Students in introductory CS courses completed CCEs as part of those courses. Students in Study 1 came from a variety of programs, and students in Study 2 were engineering majors. A profiling approach was used to test whether the impact of the CCEs could be accounted for by differences in students’ motivated and self-regulated engagement. Overall, CCEs had positive impacts on students’ grades and knowledge test scores, and although there were differences in achievement across the profiles, the impact of the CCEs was generally consistent across profiles. The CCEs appear to be a promising way to increase student achievement in introductory CS courses. Implications and directions for future research are discussed.

Background National and international child health surveys have indicated an increase in childhood obesity in China. The increase has been attributed to a rising standard of living, increasing availability of unhealthy foods, and a lack of knowledge about healthy diet. The objective of this study was to assess the effect of selected socio-demographic characteristics on the BMI, nutrition knowledge, and eating behavior of elementary school children. Methods Multistage stratified cluster sampling was used. Information on demographics, nutrition knowledge, and eating behavior was gathered by means of questionnaires. The schools’ doctors provided the height and weight data. The study was set in one economically advantaged and one economically disadvantaged province in China. The participants were Grade 3 students, ages 8–10 years (N = 3922). Results A cluster analysis identified four socio-demographic variables distinguished by parental education and family living arrangement. A one-way ANOVA compared differences among the clusters in BMI, child nutrition knowledge, and child eating behavior. Students in the cluster with lowest parent education level had the lowest nutrition knowledge scores and eating behavior scores. There was no significant benefit from college education versus high school education of parents in the other three clusters. BMI was not affected by parent education level. Conclusion The nutrition status of elementary school age children will benefit most by increasing the general level of education for those adults who are presently least educated.

This study investigated introductory computer science (CS1) students’ implicit beliefs of intelligence. Referencing Dweck and Leggett’s (1988) framework for implicit beliefs of intelligence, we examined how (1) students’ implicit beliefs changed over the course of a semester, (2) these changes differed as a function of course enrollment and students’ motivated self-regulated engagement profile, and (3) implicit beliefs predicted student learning based on standardized course grades and performance on a computational thinking knowledge test. For all students, there were significant increases in entity beliefs and significant decreases in incremental beliefs across the semester. However, examination of effect sizes suggests that significant findings for change across time were driven by changes in specific subpopulations of students. Moreover, results showed that students endorsed incremental belief more strongly than entity belief at both the beginning and end of the semester. Furthermore, the magnitude of changes differed based on students’ motivated self-regulated engagement profiles. Additionally, students’ achievement outcomes were weakly predicted by their implicit beliefs of intelligence. Finally, results showed that the relationship between changes in implicit intelligence beliefs and student achievement varied across different CS1 courses. Theoretical implications for implicit intelligence beliefs and recommendations for STEM educators are discussed.

ObjectiveAs part of a national initiative to reduce child obesity, a comprehensive school-based nutrition education intervention to change eating behaviours among grade 4 primary-school students was developed, implemented and evaluated.DesignThe intervention was developed by school staff, with technical assistance from outside health education specialists. The programme included school facility upgrades, school teacher/staff training, curriculum changes and activities for parents. Student scores on nine key eating behaviours were assessed prior to and after the programme. The quality of programme implementation in the schools was monitored by technical assistance teams.SettingShandong Province (high household income) and Qinghai Province (low household income), China. Three programme schools and three control schools in each province.ParticipantsStudents in grade 4 (age 8–9 years).ResultsThere were significant positive changes in self-reported eating behaviour scores from pre- to post-assessment in programme schools. At post-test students in programme schools had significantly higher scores than students in control schools after controlling for other variables. The programme was more effective in the high-income province. Observations by the technical assistance teams suggested the programme was implemented more completely in Shandong. The teams noted the challenges for implementing and evaluating programmes like these.ConclusionsThis intervention increased healthy eating behaviours among 4th graders in both provinces and had more effect in the more affluent province. Results suggest that a scaled-up initiative using existing school and public health resources could change eating practices in a large population over time. The intervention also provided lessons for implementing and evaluating similar nutrition programmes.

This study explored bystanders’ willingness to help a friend who flushes when drinking to reduce his/her drinking. Alcohol-related facial flushing is an indicator of an inherited variant enzyme, aldehyde dehydrogenase (ALDH), that impairs alcohol metabolism and increases drinkers’ lifetime risk of certain aerodigestive cancers. Individuals who flush should reduce their alcohol exposure, but they may continue to drink if social pressures and rules of etiquette make not drinking socially risky. The analysis used data from 2912 undergraduate students from 13 universities in southwestern, central and northeastern China from a survey asking how they respond to someone’s flushing in various scenarios. Latent class analysis grouped students by similar responses to flushing. A multinomial logistic regression explored how class membership was associated with knowledge, drinking status, and reactions to one’s own flushing. Five classes were derived from the latent class analysis, ranging from always intervene to mostly hesitate to help; in between were classes of students who were willing to help in some scenarios and hesitant in other scenarios. Only 11.6% students knew the connection between facial flushing and impaired alcohol metabolism, and knowledgeable students were somewhat more likely to assist when they saw someone flushing. In the absence of knowledge, other factors—such as drinking status, the gender of the bystander, the gender of the person who flushed, and degree of friendship with the person who flushed—determined how willing a person was to help someone reduce or stop drinking. Class membership was predicted by knowledge, gender, drinking status, and reactions to one’s own flushing. Of these 4 factors, knowledge and reactions to one’s own flushing could be influenced through alcohol education programs. It will take some time for alcohol education to catch up to and change social and cultural patterns of drinking. Meanwhile, motivational strategies should be developed to increase the willingness of bystanders to assist friends and to create a social expectation that flushers should stop or reduce their drinking.

The purpose of the present study was to investigate how the inclusion of computational creativity exercises (CCEs) merging computational and creative thinking in undergraduate computer science (CS) courses affected students' course grades, learning of core CS knowledge, self-efficacy, and creative competency. CCEs were done in lower- and upper-division CS courses at a single university. Students in CCE implementation courses were compared to students in the same courses in different semesters. Propensity score matching was used to create comparable groups (control and implementation) based on students' GPA, motivation, and engagement. Results showed that implementing CCEs in undergraduate CS courses enhanced grades, learning of core CS knowledge, and self-efficacy for creatively applying CS knowledge. However, CCEs did not impact creative competency. The effect of the CCEs was consistent across upper- and lower-division courses for all outcomes. Unlike previous studies that only established the support for CCEs, such as positive dosage effects, the results of this study indicate that CCEs have a causal effect on students' achievement, learning, and self-efficacy, and this effect is independent of general academic achievement, motivation, and engagement. These findings establish the CCEs as a validated, evidence-based instructional method.

In this workshop, we will introduce you to a suite of Computational Creativity Exercises (CCEs) that have been shown to significantly improve student learning and achievement in introductory and advanced CS courses. CCEs address core aspects of computational thinking while exposing students to creative thinking skills, and can be adapted for use in your own courses. Activities such as writing a story in separate chapters and then merging the chapters to form a coherent whole, creating quilt-like patterns with written descriptions, or designing testing strategies for an alien health machine require students to apply computational thinking to unorthodox contexts and situations promoting creative application of CS knowledge and skills. CCEs are group-based, promote active learning, and are designed to foster collaborative problem solving necessary in today's workplace. They require no programming experience making them accessible to students including those with limited CS background and those with interests in non-CS disciplines, which can encourage more diverse participation in computing. Engage in a hands-on demo of a CCE and learn how to adapt CCEs for use in your classes, including technical support from the IC2Think Project team. Learn about the rigorous research studies behind the development, design and administration of these CCEs, including the instruments we used to evaluate the CCEs. Workshop session will include "how-to" presentations, panel-based Q&A, breakout group discussions, and hands-on activities. Let's compute, create, and collaborate!

Retaining students in computer science (CS) courses and majors is a concern for many undergraduate CS programs in the United States. A large proportion of students who initially declare a major in CS do not complete a CS degree. The impact of future-oriented motivational constructs such as career aspirations and future connectedness on retention has received relatively little research attention, but these are potential contributors to students' retention in CS courses. The purpose of this study was to investigate how future-oriented motivation related to CS students' retention in CS courses over three consecutive semesters. Students enrolled in CS courses (four 100-level courses, one 200-level course, three 300-level courses, and five 400-level courses) completed survey measures of future-oriented motivation, and course enrollment data were collected for the three semesters. Logistic regression was used to determine whether motivation variables could distinguish between students who were enrolled in at least one CS course during a given semester and students who were not enrolled in any CS courses. Results indicate that, across all three semesters, career aspirations and knowledge of CS career paths were associated with a greater likelihood of continuing to take CS courses, and stronger future connectedness was associated with a lower likelihood of continuing to take CS courses. Implications for CS educators are discussed.

Cognitive Informatics (CI) is a contemporary multidisciplinary field spanning across computer science, information science, cognitive science, brain science, intelligence science, knowledge science, cognitive linguistics, and cognitive philosophy. Cognitive Computing (CC) is a novel paradigm of intelligent computing methodologies and systems based on CI that implements computational intelligence by autonomous inferences and perceptions mimicking the mechanisms of the brain. This paper reports a set of position statements presented in the plenary panel of IEEE ICCI*CC'14 on Cognitive Informatics and Cognitive Computing. The summary is contributed by invited panelists who are part of the world's renowned researchers and scholars in the transdisciplinary field of cognitive informatics and cognitive computing.

Self-efficacy is a person's subjective confidence in their capability of effectively executing behaviors and actions including problem solving. Research has shown it to be one of the most powerful motivators of human action and strongest predictors of performance across a variety of domains. This paper reports on the computational modeling of self-efficacy based on principles derived from the Unified Learning Model (ULM) as instantiated in the multi-agent Computational ULM (C-ULM). The C-ULM simulation is unique in tying self-efficacy directly to the evolution of knowledge itself and in dynamically updating self-efficacy at each step during learning and task attempts. Self-efficacy beliefs have been associated with neural and brain level cognitive processes. Because C-ULM models statistical learning consistent with neural plasticity, the C-ULM simulation provides a model of self-efficacy that is more compatible with neural and brain level instantiation. Results from simulations of self-efficacy evolution due to teaching and learning, task feedback, and knowledge decay are presented. Implications for research into human motivation and learning, cognitive informatics, and cognitive computing are discussed.

The importance of interest and choice in motivation and learning has been the central focus of much educational and psychological research. The goal of this study was to examine the impact of choice and topic and situational interest on learning, engagement, and attitudes. Ninety undergraduate college students were randomly assigned to Choice-High Interest, No Choice-High Interest, or No Choice-Low Interest conditions, and completed reading tasks, multiple choice tests, essays, measures of situational interest, and attitude. Hypotheses were tested using path analysis. Results indicate that situational interest had strong direct and indirect effects on learning, engagement, and attitude. Topic interest had a direct effect on situational interest and indirect effect on engagement through situational interest. Choice, although having a direct effect on attitude, had no effect on situational interest, learning, or engagement. Findings confirmed the primary role of situational interest in enhancing engagement and learning, as well as positive attitudes. Topic interest appeared to work through its impact on increasing or decreasing situational interest rather than by having its own independent motivational effects. Choice made students feel more positive, but it did not produce more engagement, personal connection to the material, or learning. Implications for teaching are discussed.

Cognitive Informatics (CI) is a contemporary multidisciplinary field spanning across computer science, information science, cognitive science, brain science, intelligence science, knowledge science, cognitive linguistics, and cognitive philosophy. Cognitive Computing (CC) is a novel paradigm of intelligent computing methodologies and systems based on CI that implements computational intelligence by autonomous inferences and perceptions mimicking the mechanisms of the brain. This paper reports a set of position statements presented in the plenary panel of IEEE ICCI*CC'14 on Cognitive Informatics and Cognitive Computing. The summary is contributed by invited panelists who are part of the world's renowned researchers and scholars in the transdisciplinary field of cognitive informatics and cognitive computing.

Background Technical, nonengineering required courses taken at the onset of an engineering degree provide students a foundation for engineering coursework. Students who perform poorly in these foundational courses, even in those tailored to engineering, typically have limited success in engineering. A profile approach may explain why these courses are obstacles for engineering students. This approach examines the interaction among motivation and self-regulation constructs. Purpose (Hypothesis) This project sought to determine what motivational and self-regulated learning profiles engineering students adopt in foundational courses. We hypothesized that engineering students would adopt profiles associated with maladaptive motivational beliefs and self-regulated learning behaviors. The effects of profile adoption on learning and differences associated with student major, minor, and gender were analyzed. Design/Method Five hundred and thirty-eight students, 332 of them engineering majors, were surveyed on motivation and self-regulation variables. Data were analyzed from a learner-centered profile approach using cluster analysis. Results We obtained a five-cluster learning profile solution. Approximately 83% of engineering students enrolled in an engineering-tailored foundational computer science course adopted maladaptive profiles. These students learned less than those who adopted adaptive learning profiles. Profile adoption depended on whether a student was considering a major or minor in computer science or not. Conclusions Findings indicate the motivational and self-regulated learning profiles that engineering students adopt in foundational courses, why they do so, and what profile adoption means for learning. Our findings can guide instructors in providing motivational beliefs and self-regulated learning scaffolds in the classroom.

About 70% of the beverage alcohol consumed in China annually is spirits. Recorded spirits make up most spirit consumption, but about 25% of total alcohol consumption (1.7 L pure alcohol per capita annually) is unrecorded spirits (bai jiu), either homemade or made in unregulated distilleries. In some parts of China, the consumption of unrecorded spirits is higher than average. This paper compares the patterns of use of unrecorded distilled spirits and recorded distilled spirits among rural residents in Central China. Interviews were conducted with 3298 individuals in 21 towns/villages in 10 counties in the Hubei, Anhui, and Hebei provinces in the People’s Republic of China. Unrecorded bai jiu drinkers chose it because of its taste and its low price. It was consumed mostly by older men, mostly at home with family, more regularly and at higher alcohol by volume (ABV) compared to recorded alcohol. Recorded bai jiu drinkers were more likely to drink away from their homes, consumed more bai jiu at memorable drinking occasions, and reported feeling sick after drinking more often than unrecorded bai jiu drinkers. This comparison of patterns of use of unrecorded bai jiu and recorded bai jiu does not suggest that unrecorded bai jiu is more problematic for drinkers.

Alcohol-related facial flushing is a sign of compromised alcohol metabolism and increased risk of certain cancers. This project examined how facial flushing might be used to reduce alcohol use to lower cancer risks. Interviews with Chinese university students identified gender, friendship, and drinking purpose as important variables related to whether someone would encourage a person who flushes when drinking alcohol to stop or reduce their drinking. A questionnaire was developed that incorporated these variables into 24 drinking scenarios in which someone flushed while drinking. Students responded whether they would (a) encourage the flusher to stop or drink less; (b) do nothing while wishing they could; or (c) do nothing because there was no need. Analysis of survey responses from 2912 university students showed a three-way interaction of the variables and implied that the probability students will intervene when a drinker flushes was highest when the flusher was a female, a close friend, and the drinking purpose was for fun and lowest if the flusher was a male, the friendship was general, and the drinking purpose was risky. The results provide important details about the social factors affecting how other people respond to a person who flushes when drinking alcohol. This information is useful for those considering ways to reduce and prevent aerodigestive cancers through education and information programs.

Our research is based on an innovative approach that integrates computational thinking and creative thinking in computer science courses to improve student learning and performance. Referencing Epstein's Generativity Theory, we designed and deployed Computational Creativity Exercises (CCEs) with linkages to concepts in computer science and computational thinking. Prior studies with earlier versions of the CCEs in CS1 courses found that completing more CCEs led to higher grades and increased learning of computational thinking principles. In this study, we extended the examination of CCEs to by deploying revised CCEs across two lower division (freshmen, sophomore) and three upper division (junior, senior) CS courses. We found a linear "dosage effect" of increasingly higher grades and computational thinking/CS knowledge test scores with completion of each additional CCE. This dosage effect was consistent across lower and upper division courses. Findings supported our contention that the merger of computational and creative thinking can be realized in computational creativity exercises that can be implemented and lead to increased student learning across courses from freshmen to senior level. The effect of the CCEs on learning was independent of student general academic achievement and individual student motivation. If students do the CCEs, they appear to benefit, whether or not they are self-aware of the benefit or personally motivated to do them. Issues in implementation are discussed.

Aim: This paper describes Chinese university students' understanding of the meaning of the alcohol-related flushing response and how they reacted to their own and someone else's flushing in a group drinking situation. Method: The researcher surveyed 530 Chinese university students about their understanding of flushing and their perception of how people respond to a person who visibly flushes while drinking alcohol. Findings: Most students did not know about the physiological cause of flushing. There were significant gender differences in both reactions to and perception of responses to a person who flushes. There was no direct relationship between flushing and drinking behaviour. Conclusions: This description of flushing behaviour and responses to a flushing person is discussed in terms of educational opportunities to change behaviours that could reduce the cancer related risks of this visibly at-risk group.

Improving learning and achievement in introductory computer science by incorporating creative thinking into the curriculum.

The goal of the present study was to utilize a profiling approach to understand differences in motivation and strategic self-regulation among post-secondary STEM students in major versus required non-major computer science courses. Participants were 233 students from required introductory computer science courses (194 men; 35 women; 4 unknown) at a large Midwestern state university. Cluster analysis identified five profiles: (1) a strategic profile of a highly motivated by-any-means good strategy user; (2) a knowledge-building profile of an intrinsically motivated autonomous, mastery-oriented student; (3) a surface learning profile of a utility motivated minimally engaged student; (4) an apathetic profile of an amotivational disengaged student; and (5) a learned helpless profile of a motivated but unable to effectively self-regulate student. Among CS majors and students in courses in their major field, the strategic and knowledge-building profiles were the most prevalent. Among non-CS majors and students in required non-major courses, the learned helpless, surface learning, and apathetic profiles were the most prevalent. Students in the strategic and knowledge-building profiles had significantly higher retention of computational thinking knowledge than students in other profiles. Students in the apathetic and surface learning profiles saw little instrumentality of the course for their future academic and career objectives. Findings show that students in STEM fields taking required computer science courses exhibit the same constellation of motivated strategic self-regulation profiles found in other post-secondary and K-12 settings.

We explored CS1 students' perceived instrumentality (PI) for the course and aspirations for a career related to CS. Perceived instrumentality refers to the connection one sees between a current activity and a future goal. There are two types of PI: endogenous and exogenous. Endogenous instrumentality refers to the perception that mastering new information or skills is important for achieving distal goals. Exogenous instrumentality refers to the perception that obtaining an external reward (such as a grade) is essential for obtaining future goals. We investigated (1) how students' PI and career aspirations changed over the course of a semester, (2) how these changes differed as a function of course enrollment and major (CS or not), (3) the relationship between PI and career aspirations, and (4) whether PI and career aspirations predicted academic achievement. Overall and for most subgroups, exogenous instrumentality increased significantly and endogenous instrumentality decreased significantly across the semester, though the degree of change varied among some subgroups. Career aspirations decreased overall and for most subgroups, but CS majors showed a much smaller decrease than non-majors, and students in a CS/business honors course showed an overall increase in career aspirations. Finally, students' achievement outcomes were predicted by their PI and career aspirations. These findings contribute to the literature on motivation in CS1 courses and points to PI as a promising avenue for influencing student motivation. Implications for student motivation and retention in CS and other STEM courses are also discussed.

Chunking has emerged as a basic property of human cognition. Computationally, chunking has been proposed as a process for compressing information also has been identified in neural processes in the brain and used in models of these processes. Our purpose in this paper is to expand understanding of how chunking impacts both learning and performance using the Computational-Unified Learning Model (C-ULM) a multi-agent computational model. Chunks in C-ULM long-term memory result from the updating of concept connection weights via statistical learning. Concept connection weight values move toward the accurate weight value needed for a task and a confusion interval reflecting certainty in the weight value is shortened each time a concept is attended in working memory and each time a task is solved, and the confusion interval is lengthened when a chunk is not retrieved over a number of cycles and each time a task solution attempt fails. The dynamic tension between these updating mechanisms allows chunks to come to represent the history of relative frequency of co-occurrence for the concept connections present in the environment; thereby encoding the statistical regularities in the environment in the long-term memory chunk network. In this paper, the computational formulation of chunking in the C-ULM is described, followed by results of simulation studies examining impacts of chunking versus no chunking on agent learning and agent effectiveness. Then, conclusions and implications of the work both for understanding human learning and for applications within cognitive informatics, artificial intelligence, and cognitive computing are discussed.