Rebecca Vivian

University Students’ Informal Learning Practices Using Facebook: Help or Hindrance?

Facebook (FB) has gained worldwide popularity and Higher Education Institutions have an interest in the Social Network Site’s (SNSs) potential to support student learning and peer networking. This research paper reports on the findings from one online discussion group with 15 students from the University of South Australia about their preferences, experiences and use of FB for informal learning. This research found that students accessed and used FB in different ways. FB was used for informal learning via the use of status updates, private messaging, instant chat, tagging and FB ‘groups’. Students in the group often viewed FB as a source of procrastination; however, some students felt the benefits of FB to support their learning outweighed the issue of the SNS as a distraction. Some students reported that they increased their use of FB during assessment periods and a number of students used ‘SNS self-control’ practices that inhibited or reduced their use of FB.

Collaborative learning and anxiety: a phenomenographic study of collaborative learning activities

Collaborative learning encourages deeper learning, producing significant benefit in learning outcomes. There has been an increasing trend to adopt collaborative activities, due to the expected learning benefits but also because of the expected social benefits and their impact on transition concerns. However, collaborative activities may also introduce additional stress and anxiety for students as they cope with altered participation expectations, and the need to develop collaboration, communication and management skills concurrently with their discipline skills. In this paper we describe a phenomenographic analysis of students reflections on collaborative activities, including their perceptions of the purpose of such activities, and corresponding behaviours.

Increasing the effectiveness of automated assessment by increasing marking granularity and feedback units

Computer-based assessment is a useful tool for handling large-scale classes and is extensively used in the automated assessment of student programming assignments in Computer Science. The forms that this assessment takes, however, can vary widely from simple acknowledgement to a detailed analysis of output, structure and code. This study focusses on output analysis of submitted student assignment code and the degree to which changes in automated feedback influence student marks and persistence in submission. Data was collected over a four year period, over 22 courses but we focus on one course for this paper. Assignments were grouped by the number of different units of automated feedback that were delivered per assignment to investigate if students changed their submission behaviour or performance as the possible set of marks, that a student could achieve, changed. We discovered that pre-deadline results improved as the number of feedback units increase and that post-deadline activity was also improved as more feedback units were available.

Identifying computer science self-regulated learning strategies

Computer Science students struggle to develop fundamental programming skills and software development processes. Crucial to successful mastery is the development of discipline specific cognitive and metacognitive skills, including self-regulation. We can assist our students in the process of reflection and self-regulation by identifying and articulating successful self-regulated learning strategies for specific discipline contexts. However, in order to do so, we must develop an understanding of those discipline-specific strategies that are successful and can be readily adopted by students. In this paper, we analyse student reflections from an introductory software development course, identifying the usage of self-regulated learning strategies that are either specific to the software development domain, or articulated in that context. This study assists in the understanding of how Computer Science students develop learning skill within the discipline, and provides examples to guide the development of scaffolding activities to assist learning development.

Evolution of software development strategies

The development of discipline-specific cognitive and meta-cognitive skills is fundamental to the successful mastery of software development skills and processes. This development happens over time and is influenced by many factors, however its understanding by teachers is crucial in order to develop activities and materials to transform students from novice to expert software engineers. In this paper, we analyse the evolution of learning strategies of novice, first year students, to expert, final year students. We analyse reflections on software development processes from students in an introductory software development course, and compare them to those of final year students, in a distributed systems development course. Our study shows that computer science - specific strategies evolve as expected, with the majority of final year students including design before coding in their software development process, but that several areas still require scaffolding activities to assist in learning development.

A review of Computer Science resources for learning and teaching with K-12 computing curricula: an Australian case study

To support teachers to implement Computer Science curricula into classrooms from the very first year of school, teachers, schools and organisations seek quality curriculum resources to support implementation and teacher professional development. Until now, many Computer Science resources and outreach initiatives have targeted K-12 school-age children, with the intention to engage children and increase interest, rather than to formally teach concepts and skills. What is the educational quality of existing Computer Science resources and to what extent are they suitable for classroom learning and teaching? In this paper, an assessment framework is presented to evaluate the quality of online Computer Science resources. Further, a semi-systematic review of available online Computer Science resources was conducted to evaluate resources available for classroom learning and teaching and to identify gaps in resource availability, using the Australian curriculum as a case study analysis. The findings reveal a predominance of quality resources, however, a number of critical gaps were identified. This paper provides recommendations and guidance for the development of new and supplementary resources and future research.

A Method to Analyze Computer Science Students’ Teamwork in Online Collaborative Learning Environments

Although teamwork has been identified as an essential skill for Computer Science (CS) graduates, these skills are identified as lacking by industry employers, which suggests a need for more proactive measures to teach and assess teamwork. In one CS course, students worked in teams to create a wiki solution to problem-based questions. Through a case-study approach, we test a developed teamwork framework, using manual content analysis and sentiment analysis, to determine if the framework can provide insight into students’ teamwork behavior and to determine if the wiki task encouraged students to collaborate, share knowledge, and self-adopt teamwork roles. Analysis revealed the identification of both active and cohesive teams, disengaged students, and particular roles and behaviors that were lacking. Furthermore, sentiment analysis revealed that teams moved through positive and negative emotions over the course of developing their solution, toward satisfaction. The findings demonstrate the value of the detailed analysis of online teamwork. However, we propose the need for automated measures that provide real-time feedback to assist educators in the fair and efficient assessment of teamwork. We present a prototype system and recommendations, based on our analysis, for automated teamwork analysis tools.

The development of a dashboard tool for visualising online teamwork discussions

Many software development organisations today adopt global software engineering (GSE) and agile models, requiring software engineers to collaborate and develop software in flexible, distributed, online teams. However, many employers have expressed concern that graduates lack teamwork skills and one of the most commonly occurring problems with GSE models are issues with project management. Team managers and educators often oversee a number of teams and the large corpus of data, in combination with agile models, make it difficult to efficiently assess factors such as team role distribution and emotional climate. Current methods and tools for monitoring software engineering (SE) teamwork in both industry and education settings typically focus on member contributions, reflection, or product outcomes, which are limited in terms of real-time feedback and accurate behavioural analysis. We have created a dashboard that extracts and communicates team role distribution and team emotion information in real-time. Our proof of concept provides a real-time analysis of teamwork discussions and visualises team member emotions, the roles they have adopted and overall team sentiment during the course of a collaborative problem-solving project. We demonstrate and discuss how such a tool could be useful for SE team management and training and the development of teamwork skills in SE university courses.

Computer Science Education: The First Threshold Concept

When presented with results and evidence that clearly show how teaching and learning can be improved, it is not uncommon for such ideas to be rejected because of personal experience, inter-disciplinary suspicion or because the information seems to completely counter all previously accepted wisdom. Such behaviour in students could be classified as a reaction to alien and counter-intuitive knowledge, as described in the works of Meyer and Land on threshold concepts. Since the threshold concept is, itself, a product of educational research, we would expect to have difficulty in explaining this concept to our colleagues. This is one possible explanation for the relatively slow penetration of computer science specific educational theory into modern computer science teaching practice. In this paper we examine the application of the threshold concept theory to the whole of our field of education, using the literature to find examples of how troublesome knowledge does, or does not, spread throughout the academic community. We track the adoption and display of knowledge of key concepts in Computer Science educational research, in order to identify common patterns in adoption and, by providing models to explain the flow of information across our discipline, provide an early indication of the role that threshold concepts (as a barrier to understanding) are playing in the community.

Can everybody learn to code?: computer science community perceptions about learning the fundamentals of programming

Recently, we have seen a wave of initiatives that encourage everybody (from children to adults) to learn to code and many countries implement new K-12 computing curricula. However, research has identified the numerous challenges experienced by students learning to code. With much of the literature focused on student perceptions and capabilities, what insight might the computer science (CS) community offer about learning to code that may guide future directions in K-12 practice and research? We invited the CS community to respond to an online survey about learning to code. This survey forms a pilot to determine whether the topic warrants further exploration. We explore the responses in light of the introductory programming literature and Mindset Theories to identify perceived capabilities required, the challenges and potential barriers to learning to code. Our results were based on a small sample, mostly from Australian academics and IT professionals. A majority perceived that anybody could learn to code, with effort and motivation, however, that more advanced levels of programming require mathematical logic, a desire and ability for problem-solving and abstract thinking. A variety of challenges were identified, which may have implications for CS education and research. The findings warrant further exploration into the area of CS community perceptions, particularly with educators of introductory programming courses.