Does gender matter in online learning?

It is generally noted that computing is gendered, with women opting out of IT. Will the impact of online learning change this? Some researchers claim that women are disadvantaged in online courses. Others argue that we need a ‘women‐friendly cyber‐classroom’. Yet our experience is that the women achieve better results than the men; it is loner males that are disadvantaged by distance learning. We argue that online courses need to be people‐friendly so that no learners are disadvantaged

The Case for Improving U.S. Computer Science Education

Despite the growing use of computers and software in every facet of our economy, not until recently has computer science education begun to gain traction in American school systems. The current focus on improving science, technology, engineering, and mathematics (STEM) education in the U.S. school system has disregarded differences within STEM fields. Indeed, the most important STEM field for a modern economy is not only one that is not represented by its own initial in "STEM" but also the field with the fewest number of high school students taking its classes and by far has the most room for improvement—computer science

Engaging Girls in Computer Science: Do Single-Gender Interdisciplinary Classes Help?

Computing-driven innovation cannot reach its full potential if only a fraction of the population is involved. Without girls and their non-stereotypical contribution, the innovation potential is severely limited. In computer science (CS) and software engineering (SE), the gender gap persists without any positive trend. Many girls find it challenging to identify with the subject of CS. However, we can capitalize on their interests and create environments for girls through interdisciplinary subcultures to spark and foster enthusiasm for CS. This paper presents and discusses the results of an intervention in which we applied a novel interdisciplinary online course in data science to get girls excited about CS and programming by contributing to the grand goal of solving colony collapse disorder from biology and geoecology. The results show the potential of such programs to get girls excited about programming, but also important implications in terms of the learning environment. The startling results show that girls from single-gender classes (SGCs) are significantly more open to CS-related topics and that the intervention evoked significantly more positive feelings in them than in girls from mixed-gender classes (MGCs). The findings highlight the importance of how CS-related topics are introduced in school and the crucial impact of the learning environment to meet the requirements of truly gender-inclusive education

Framework to Enhance Teaching and Learning in System Analysis and Unified Modelling Language

Cowling, MA ORCiD: 0000-0003-1444-1563; Munoz Carpio, JC ORCiD: 0000-0003-0251-5510Systems Analysis modelling is considered foundational for Information and Communication Technology (ICT) students, with introductory and advanced units included in nearly all ICT and computer science degrees. Yet despite this, novice systems analysts (learners) find modelling and systems thinking quite difficult to learn and master. This makes the process of teaching the fundamentals frustrating and time intensive. This paper will discuss the foundational problems that learners face when learning Systems Analysis modelling. Through a systematic literature review, a framework will be proposed based on the key problems that novice learners experience. In this proposed framework, a sequence of activities has been developed to facilitate understanding of the requirements, solutions and incremental modelling. An example is provided illustrating how the framework could be used to incorporate visualization and gaming elements into a Systems Analysis classroom; therefore, improving motivation and learning. Through this work, a greater understanding of the approach to teaching modelling within the computer science classroom will be provided, as well as a framework to guide future teaching activities

A Study of Pair Programming Enjoyment and Attendance using Study Motivation and Strategy Metrics

We explore educational pair programming in a university context with high student autonomy and individual responsibility. The data comes from two separate introductory programming courses with optional pair programming assignments. We analyze lab attendance and course outcomes to determine whether students' previous programming experience or gender influence attendance. We further compare these statistics to self-reported data on study motivation, study strategies, and student enjoyment of pair programming. The influence of grading systems on pair programming behavior and course outcomes is also examined. Our results suggest that gender and previous programming experience correlate with participation in pair programming labs. At the same time, there are no significant differences in self-reported enjoyment of pair programming between any of the groups, and the results from commonly used study motivation and strategy questionnaires provide little insight into students/ actual behavior.Peer reviewe

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

Examining Female Students' Motivation and Preferences for Course Choices in an Undergraduate ICT Program in a Californian University

This paper reports on a study of female students’ motivations and preferences for course and career choices in an Information Communications and Technology (ICT) undergraduate program. Descriptive-interpretive phenomenology was adopted to investigate the phenomenon. Bandura’s self-efficacy framework was influential in interpreting participants’ motivation toward course choices and preferences. Findings revealed intrinsic and extrinsic motivation as significant influences on participants’ decisions to go into either technical or design majors of the ICT field. Extrinsic motivation came from influences such as stereotyping of gender abilities, prior computing skills, and role models while intrinsic motivation was based on individuals’ career interests and self-efficacy in specific sectors. Findings reflected that the majority of female participants preferred the design track within the ICT career field (web design, computer animation, and instructional design), with interest in self-employment. A very small number of female participants enrolled in the technical track involving computer programming, networking, and database administration, indicating female students’ preference for the design aspects of ICT