First-Year Computer Science Students: Pathways and Perceptions in Introductory Computer Science Courses

This study examined student perceptions and experiences of an introductory Computer Science course at the University of Maine; COS 125: Introduction to Problem Solving Using Computer Programs. It also explored the pathways that students pursue after taking COS 125, depending on their success in the course, and their motivation to persist. Through characterizing student populations and their performance in their first semester in the Computer Science program, they can be placed into one of three categories that explain their path; a “continuer” (passed COS 125 and decided to stay in the major), a “persister” (did not pass COS 125 and decided to stay in the major), or a “withdrawer” (left the major regardless of their grade). After categorizing student populations based on their characteristics and chosen pathway, identifying behaviors of successful students will assist in making suggestions for future students to ensure their success. While there are current obstacles in the Computer Science field that affect student success (e.g. lack of preparation, self-efficacy, and family background), the creation of a model will help to predict student pathways and assist in the success and retention of future cohorts. Based on the findings, suggestions are provided to assess the actions and characteristics of students helps to create suggestions for students who need support in their pursuit to achieve a Computer Science degree

Harnessing Technology: new modes of technology-enhanced learning: action research, March 2009

5 action research studie

Keeping Data Science Broad: Negotiating the Digital and Data Divide Among Higher Education Institutions

The goal of the “Keeping Data Science Broad” series of webinars and workshops was to garner community input into pathways for keeping data science education broadly inclusive across sectors, institutions, and populations. Input was collected from data science programs across the nation, either traditional or alternative, and from a range of institution types including community colleges, minority-led and minority-serving institutions, liberal arts colleges, tribal colleges, universities, and industry partners. The series consisted of two webinars (August 2017 and September 2017) leading up to a workshop (November 2017) exploring the future of data science education and workforce at institutions of higher learning that are primarily teaching-focused. A third follow-up webinar was held after the workshop (January 2018) to report on outcomes and next steps. Program committee members were chosen to represent a broad spectrum of communities with a diversity of geography (West, Northeast, Midwest, and South), discipline (Computer Science, Math, Statistics, and Domains), as well as institution type (Historically Black Colleges and Universities (HBCU’s), Hispanic-Serving Institutions (HSI’s), other Minority-Serving Institutions (MSI\u27s), Community College\u27s (CC’s), 4-year colleges, Tribal Colleges, R1 Universities, Government and Industry Partners)

Keeping Data Science Broad: Negotiating the Digital and Data Divide Among Higher Education Institutions

The goal of the “Keeping Data Science Broad” series of webinars and workshops was to garner community input into pathways for keeping data science education broadly inclusive across sectors, institutions, and populations. Input was collected from data science programs across the nation, either traditional or alternative, and from a range of institution types including community colleges, minority-led and minority-serving institutions, liberal arts colleges, tribal colleges, universities, and industry partners. The series consisted of two webinars (August 2017 and September 2017) leading up to a workshop (November 2017) exploring the future of data science education and workforce at institutions of higher learning that are primarily teaching-focused. A third follow-up webinar was held after the workshop (January 2018) to report on outcomes and next steps. Program committee members were chosen to represent a broad spectrum of communities with a diversity of geography (West, Northeast, Midwest, and South), discipline (Computer Science, Math, Statistics, and Domains), as well as institution type (Historically Black Colleges and Universities (HBCU’s), Hispanic-Serving Institutions (HSI’s), other Minority-Serving Institutions (MSI\u27s), Community College\u27s (CC’s), 4-year colleges, Tribal Colleges, R1 Universities, Government and Industry Partners)

Baseline study of employability related activities in Scottish colleges

In October 2004, the Scottish Funding Council (SFC)'s predecessor bodies, theSFEFC and the SHEFC, publishedLearning to Work(SFC 2004), a discussion paperabout how Scotland's colleges and universities can help to enhance learners'employability. In subsequent dialogue with stakeholders, there was agreement thatemployability should be a specific focus for quality enhancement in the college sectorfrom 2006-07. As a basis for further development, the SFC commissioned this studyto provide information on the range of current activities and practices in Scotland'scolleges which contribute to enhancing employability

Identification and Evaluation of Predictors for Learning Success and of Models for Teaching Computer Programming in Contemporary Contexts

Introductory undergraduate computer programming courses are renowned for higher than average failure and withdrawal rates when compared to other subject areas. The closer partnership between higher education and the rapidly expanding digital technology industry, as demonstrated by the establishment of new Degree Apprenticeships in computer science and digital technologies, requires efficient and effective means for teaching programming skills. This research, therefore, aimed to identify reliable predictors of success in learning programming or vulnerability to failure. The research also aimed to evaluate teaching methods and remedial interventions towards recommending a teaching model that supported and engaged learners in contemporary contexts that were relevant to the workplace. Investigation of qualifications designed to prepare students for undergraduate computer science courses revealed that A-level entrants achieved significantly higher programming grades than BTEC students. However, there was little difference between the grades of those with and those without previous qualifications in computing or ICT subjects. Analysis of engagement metrics revealed a strong correlation between extent of co-operation and programming grade, in contrast to a weak correlation between programming grade and code understanding. Further analysis of video recordings, interviews and observational records distinguished between the type of communication that helped peers comprehend tasks and concepts, and other forms of communication that were only concerned with completing tasks. Following the introduction of periodic assessment, essentially converting a single final assessment to three staged summative assessment points, it was found that failing students often pass only one of the three assignment parts. Furthermore, only 10% of those who failed overall had attempted all three assignments. Reasons for failure were attributed to ‘surface’ motivations (such as regulating efforts to achieve a minimum pass of 40%), ineffective working habits or stressful personal circumstances rather than any fundamental difficulty encountered with subject material. A key contribution to pedagogical practice made by this research is to propose an ‘incremental’ teaching model. This model is informed by educational theory and empirical evidence and comprises short cycles of three activities: presenting new topic information, tasking students with a relevant exercise and then demonstrating and discussing the exercise solution. The effectiveness of this model is evidenced by increased engagement, increased quiz scores at the end of each teaching session and increased retention of code knowledge at the end of the course

Perceptions Measurement of Professional Certifications to Augment Buffalo State College Baccalaureate Technology Programs, as a Representative American Postsecondary Educational Institution

The purpose of this study was to assess, measure, and analyze whether voluntary, nationally-recognized professional certification credentials were important to augment technology programs at Buffalo State College (BSC), as a representative postsecondary baccalaureate degree-granting institution offering technology curricula. Six BSC undergraduate technology programs were evaluated within the scope of this study: 1.) Computer Information Systems; 2.) Electrical Engineering, Electronics; 3.) Electrical Engineering, Smart Grid; 4.) Industrial Technology; 5.) Mechanical Engineering; and 6.) Technology Education. This study considered the following three aspects of the problem: a.) postsecondary technology program enrollment and graduation trends; b.) the value/awareness of professional certifications to employers and students; and c.) professional certification relevancy and postsecondary curricula integration. The study was conducted through surveys and interviews with four technology-related purposive sample groups: 1.) BSC program alumni; 2.) BSC and non-BSC technology program faculty; 3.) hiring managers/industry leaders; and 4.) non-BSC alumni and certification holders. In addition, this study included an analysis of relevant professional certification organizations and student enrollment data from the six technology programs within scope. Research methods included both quantitative and qualitative analytical techniques. This study concluded undergraduate technology students benefitted from a greater awareness of relevant professional certifications and their perceived value. This study also found the academic community may be well served to acknowledge the increasing trend of professional certification integration into postsecondary technology programs

Understanding Occupational and Skill Demand in New Jersey's Finance Industry

The finance industry in New Jersey employs over 200,000 people. Many more workers benefit from the state's proximity to the finance industry in New York City. Jobs in the industry are evolving rapidly in response to national and global trends, such as deregulation, increasingly complex laws, and new technologies. As jobs change, skill requirements for both entry-level and incumbent workers increase. This report summarizes the skill, knowledge, and educational requirements of key finance occupations and identifies strategies for meeting the workforce challenges facing the industry

Self-Assessment and Student Improvement in an Introductory Computer Course at the Community College-level

The purpose of this study was to determine a student‟s computer knowledge upon course entry and if there was a difference in college students‟ improvement scores as measured by the difference in pretest and posttest scores of new or novice users, moderate users, and expert users at the end of a college-level introductory computing class. This study also determined whether there were differences in improvement scores by gender or age group. The results of this study were used to determine whether there was a difference in improvement scores among the 3 campus locations participating in this study. Four hundred sixty-nine students participated in this study at a community college located in Northeast Tennessee. A survey, pretest, and posttest were administered to students in a collegelevel introductory computing class. The survey consisted of demographic data that included gender, age category, location, Internet access, educational experience, and the self-rated user category, while the pretest and posttest explored the student‟s knowledge of computer terminology, hardware, the current operating system, Microsoft Word, Microsoft Excel, and Microsoft PowerPoint. The data analysis revealed significant differences in pretest scores between educational experience categories. In each instance, the pretest mean for first semester freshmen students was lower than second semester freshmen and sophomores. The study also reported significant differences between the self-rated user categories and pretest scores as well as differences in improvement scores (posttest scores minus pretest scores), which were higher for new or novice users. Of the 3 participating campus locations, students at Location 1 earned higher improvement scores than did students at Location 2. The results also indicated that there was a significant difference between the types of course delivery and course improvement scores (posttest scores minus pretest scores). The improvement scores for on ground delivery was 5 points higher than the hybrid course delivery. Finally, the gender and age categories as compared to the self-rated user categories revealed no significant differences in the study