Source code plagiarism detection (SCPD) is a crucial challenge in computer science education that affects academic integrity. It can be considered as an Information Retrieval (IR) task. One of the IR approaches is the Semantic Similarity Search (S-3), which aims to retrieve related results, given a query. It can be applied to SCPD by obtaining the most similar pairs given a large collection of codes.

The education system of Tanzania uses computing artifacts to support curricula. Computer science, as one of the fields of study, uses high-performance computing artifacts as a learning tool. However, there is a need for knowledge on designing an HPC artifact in the education context. In this study, we designed and deployed a micro HPC artifact, which is portable and used a credit-card-sized computer and the Linux operating system. The designing phase used the micro HPC artifact to gather knowledge and skills learned by students on how to improve the design. This paper aims to explain the processes of designing micro HPC artifacts as educational tools using the design science research methodology. In this study, we utilized focus groups to gather information regarding improving the design of micro HPC artifacts using the DSR paradigm. The design outcome of this paper can be used as a manual for improving the design of micro HPC artifacts for computer science education.

Many universities still struggle with the issue of how to facilitate the sharing of knowledge gained by instructors and maximize the value gained from all available such knowledge assets. Poor Knowledge Sharing (KS) can deter the successful implementation of teaching expertise, and this can affect instructors' teaching performance and may result in lower levels of learner achievement than could otherwise be achieved. Therefore, there is a need to implement a knowledge management (KM) initiative that facilitates the sharing of teaching practices among university instructors. In order to address this issue, this paper proposes a comprehensive and practical Computer-based Teaching Practices Management System (TPMS) which aims to foster instructors' participation in KS practices by employing a gamification approach. A design science research methodology is adopted in order to understand what would drive instructors to share their knowledge; this information is used in order to map their behavior to system features. A qualitative evaluation of users' experiences of utilizing the proposed features shows that the instructors express satisfaction with the motivational affordances and feel that they were motivated to participate in knowledge sharing activities.

This research in progress paper describes a teaching practices management framework (TPMF) which strongly supports the sharing processes related to Teaching Practices (TPs) - those that can be performed with the help of an information system. Managing with respect to TPs, so that teachers' accumulated experience may be identified, shared and reused, can offer significant benefits, including the introduction of teaching innovations which lead to improvements in overall teaching quality, and the enhancement of academics' professional development efforts. In this paper, we aim to define a teaching practices management framework (TPMF) for enhancing the sharing processes relating to TPs. The development of this TPMF has been informed by semi-structured interviews conducted with 22 instructors working in two universities in Saudi Arabia; these interviews were undertaken in order to better understand the academics' actual knowledge sharing behaviors in relation to TPs and also to gain a systemic and overall perspective of current knowledge sharing approaches. An inductive coding approach was employed to help the researcher extract themes which were mentioned by the interviewees. It is believed that this framework may well be of great assistance to higher education sector institutions.

This full research paper focuses on the design of a Teaching Practices Management System (TPMS) which supports the sharing of teaching practices (TPs) amongst computer science instructors. Many years of valuable TPs can be lost due to academic retirement when no competent knowledge management system is available for recording these TPs. Consequently, novice teachers are currently facing critical challenges when delivering subject knowledge that relates to algorithms, programming and the development of computational thinking skills without the benefit of others' experience. After a study of the relevant literature, it could be seen that far too little attention has been paid to the capturing and sharing of TPs which are not easily expressed or communicated in visual or verbal terms. Thus, we design and then demonstrate a Teaching Practices Management System (TPMS) which supports the capturing of TPs. A quantitative and a qualitative evaluation of users' experiences of employing the system shows that instructors are satisfied with it and are mostly positive about its features. The findings of this study hold considerable promise in relation to developing engaging and effective knowledge sharing systems for use by academic instructors.

Reflective writing is vital in learning professional skills and particularly in Computer Science (CS). However, there appears to be a lack of literature relating to a reliable of the current reflective writing frameworks used for CS education. This paper describes a novel Reflective Writing Framework (RWF) that has been applied to the manual content analysis of CS students' reflective writings. The paper aims to empirically examine this RWF in terms of reflection indicators and levels that can be manually assessed by raters. The results of this manual content analysis showed empirically that the coding scheme of the RWF is valid and reliable. The results were that the inter-rater reliability (IRR) of the overall coding scheme of the RWF increased from 0.5 to 0.8 in pilot tests and ranged between 0.40 and 0.75 in terms reflection indicators and levels; substantially, this means ranged from moderate to substantial agreement. This research contributes to CS education an RWF that can be reliably annotated and was validated by CS experts.

This Research to Practice Full Paper presents the experience of implementing micro HPC (μHPC) clusters in the education context. In developing countries, access to and experience of High Performance Computing (HPC) facilities (which are important for the economic development of those countries) has presented challenges to academic institutions due to prohibitive costs of acquisition and maintenance of HPC systems. These challenges affect the delivery of courses, which include HPC and parallel computation in their syllabi. However, due to advancements in integrated circuit technologies, credit-card-sized personal computers (PCs) have emerged with the capabilities of a fully-fledged PC. These credit-card-sized PCs offer an opportunity for system integrators to build micro HPC (μHPC) clusters which, apart from their efficiency, scalability and availability, have a number of attributes which are not shared with conventional data-center based HPC clusters These include their low power consumption, portability, diskless nodes, cost-effectiveness and excellent price to performance ratios. μHPC clusters are, therefore, ideally suited to support curricula in all educational disciplines that demand parallel computation. The purpose of this study is to investigate the implementation of μHPC to find out from students how ease of use of a μHPC system is to acquire skills and knowledge of HPC. We used focus groups and surveys to gather data in the framework of the design science research paradigm. The implementation of μHPC clusters involved a demonstration of the system in the problem context that provided valuable lessons. The results indicate that μHPC is the ease of use HPC artifact for learning about management, integration, deployment, installation, downloading, and running of parallel programs.

Many universities still face difficulties when attempting to improve the sharing of knowledge accumulated by instructors, due to geographical and social constraints. Insufficient knowledge sharing can significantly hinder the successful implementation of teaching expertise, and this can affect instructors' teaching performance and may result in lower levels of learner attainment than could otherwise have been achieved. In this design science research, we therefore propose (1) a prototypical teaching practices management framework (TPMF) and (2) a set of design principles and features for an information system that support the sharing of BTPs and may constitute a viable alternative to traditional approaches. The development of TPMF, the design principles and features has been informed by interviews conducted with 22 instructors. In this research-in-progress paper, we present our preliminary results and discuss next steps.

In this poster we present a novel conceptual framework for enhanc- ing the sharing of best teaching practices among academics. The proposed framework is constructed based upon the understanding and mapping of the [1] knowledge creation theory.

Many disciplines already embed reflective practice in their curriculum as it is important for the professional development of their students. Many frameworks have been developed to capture reflective practice, but there is a lack of knowledge about what constitutes it in computer science education (CSE). This poster introduces a reflective writing framework (RWF) in CSE. This poster makes two contributions: (1) it outlines the construction process of the RWF for CSE, and (2) it discusses the proposed validation of the RWF with a panel of experts.

Teachers deal with plagiarism on a regular basis, so they try to prevent and detect plagiarism, a task that is complicated by the large size of some classes. Students who cheat often try to hide their plagiarism (obfuscate), and many different similarity detection engines (often called plagiarism detection tools) have been built to help teachers. This article focuses only on plagiarism detection and presents a detailed systematic review of the field of source-code plagiarism detection in academia. This review gives an overview of definitions of plagiarism, plagiarism detection tools, comparison metrics, obfuscation methods, datasets used for comparison, and algorithm types. Perspectives on the meaning of source-code plagiarism detection in academia are presented, together with categorisations of the available detection tools and analyses of their effectiveness. While writing the review, some interesting insights have been found about metrics and datasets for quantitative tool comparison and categorisation of detection algorithms. Also, existing obfuscation methods classifications have been expanded together with a new definition of “source-code plagiarism detection in academia.”

Plagiarism has become an increasing problem in higher education in recent years. Coding style can be used to detect source code plagiarism that involves writing and deciding the structure of the code which does not affect the logic of a program, thus offering a way to differentiate between different code authors. This paper focuses to identify whether a data set consisting of student programming assignments is rich enough to apply coding style metrics to detect similarities between code sequences, and we use the BlackBox dataset as a case study.

Open data are playing a vital role in different communities, including governments, businesses and education. This revolution has had a high impact on the education field. Recently, Linked Data are being adopted for publishing and connecting data on the web by exposing and connecting data, which were not previously linked. In the context of education, applying Linked Data to the growing amount of open data used for learning is potentially highly beneficial. This paper proposes a system that tackles the challenges of data acquisition and integration from distributed web data sources into one linked data set. The application domain of this work is medical education, and the focus is on integrating educational content in the form of articles published in online educational libraries and Web 2.0 content that can be used for education. The process of integrating a collection of heterogeneous resources is to create links that connect the resources collected from distributed web data sources based on their semantics. The proposed system harvests metadata from distributed web sources and enriches it with concepts from biomedical ontologies, such as Systematized Nomenclature of Medicine—Clinical Terms (SNOMED CT), that enable its linking. The final result of building this system is a linked data set of more than 10 000 resources collected from PubMed Library, YouTube channels and Blogging platforms. The final linked data set is evaluated by developing information retrieval methods that exploit the SNOMED CT hierarchical relations for accessing and querying the data set. Ontology-based browsing method has been developed for exploring the data set, and the browsing results have been clustered to evaluate its linkages. Furthermore, ontology-based query searching method has been developed and tested to enhance the discoverability of the data. The results were promising and had shown that using SNOMED CT for integrating distributed resources on the web is beneficial.

Perspectives of students on what constitutes source-code plagiarism may differ based on their educational background. Surveys have been conducted with home students undertaking computing and joint computing subject degrees at higher education institutions throughout the UK, China, and South Cyprus, and a total of 984 responses have been statistically analysed to determine the common areas of understanding and misunderstanding among students on various topics related to source-code plagiarism. The study identifies those topics which are well understood, and those topics which are not properly understood across the different groups of students, and is the first study which specifically discusses Cypriot student perceptions on source-code plagiarism. This study provides useful information to educators (teaching home and international students) who wish to better inform their students on the issues of plagiarism and source-code plagiarism. Finally, the survey results revealed that although students who were informed about plagiarism better understood what actions constitute plagiarism, some topics were still unclear among students regardless of the students’ educational background and whether they had been previously informed about plagiarism.

The use of online course material is the approach adopted by most universities to support students’ revision, and teachers usually have the responsibility for designing or uploading online materials on their own course websites. However, some teachers might lack programming skills or motivation, and most current online materials are just uploaded in a static format (such as PDF) which is not suitable for all students. Moreover, during revision periods students may be faced with a lot of unorganised materials to be revised in a short period of time, and this can lead to an ineffective revision process. In order to address these issues, this paper proposes a software framework that aims to maximise the benefit of current online materials when used to support student revision. This framework is called SRECMATs (Self-Revision E-Course MATerials) and has been deployed as a tool that allows teachers to automatically create an intelligent tutoring system to manage online materials without any programming knowledge, and to support students to navigate easily through these online materials during their revision. This paper evaluates the proposed framework in order to understand students’ perceptions with regard to the use of the system prototype, and the results indicate which features are suitable for providing online revision materials as well as confirming the benefit of the revision framework.

M-learning plays a progressively significant role in the advancement of teaching and learning in higher education. However, the effective implementation of m-learning in higher education will be based on users' experiences and motivation to use this technology. Though m-learning has become global, developing countries such as Nigeria are yet to enjoy the full potential offered by m-learning. This study is focused on ascertaining students' experiences with m-learning, determining the influence of m-learning on students' motivations and interests, and identifying factors that are limiting m-learning adoption in Nigeria. We investigated these experiences by analysing questionnaires collected from undergraduate and postgraduate students of six universities in Nigeria. The results from our study show that the students own and use diverse mobile devices to engage in educational activities and other social networking purposes. Some of these learning activities are sending SMS messages, playing educational games, social learning, reading e-books/pdfs, and completing assignments and quizzes. Students expressed their satisfaction with m-learning especially for supporting them to learn anywhere, anytime. They further confirmed that m-learning motivates, interests, and inspires every aspect of learning. Furthermore, the students acknowledges that the interactivity, flexibility, convenience and engagement of m-learning were authentic learning experiences.

Digital materials not only provide opportunities as enablers of e-learning development, but also create a new challenge. The current e-materials provided on a course website are individually designed for learning in classrooms rather than for revision. In order to enable the capability of e-materials to support a students revision, we need an efficient system to associate related pieces of different e-materials. In this case, the features of each item of e-material, including the structure and the technical terms they contain, need to be studied and applied in order to calculate the similarity between relevant e-materials. Even though difficulties regarding technical term extraction and the similarities between two text documents have been widely discussed, empirical experiments for particular types of e-learning materials (for instance, lecture slides and past exam papers) are still rare. In this paper, we propose a framework and relatedness model for associating lecture slides and past exam paper materials to support revision based on Natural Language Processing (NLP) techniques. We compare and evaluate the efficiency of different combinations of three weighted schemes, term frequency (TF), inverse document frequency (IDF), and term location (TL), for calculating the relatedness score. The experiments were conducted on 30 lectures (~900 slides) and 3 past exam papers (12 pages) of a data structures course at the authors’ institution. The findings indicate the appropriate features for calculating the relatedness score between lecture slides and past exam papers.

A review of the practical uses of errors in education reveals three contexts where errors have been shown to help: teaching conceptual knowledge, changing students' attitudes and promoting learning skills. Conflictive animations form a novel approach to teaching programming that follows a long tradition on research and development on program animation tools. Conflictive animations link the benefits of errors with program animation tools and programming education. This approach involves presenting to the students conflictive animations that do not animate faithfully the programs or concepts taught. Conflictive animations are versatile enough to cover the fundamental building blocks of programs such as operators, expressions and statements. With conflictive animations a novel set of learning activities can be introduced to computer science classes. This conflictive dimension of activities augments an engagement taxonomy for animation tools at all levels. They are an example of activities that promote critical thinking. A particular implementation of conflictive animations has been empirically evaluated aiming for ecological validity rather than statistical significance. Results indicate that students using conflictive animations improve their metacognitive skills, and, when compared to a control group, their conceptual knowledge improves at a better rate.

Recent work has highlighted how consideration of learning styles in the process of group formation for collaborative learning can have a positive impact. This paper investigates the performance of similar learning style groups and diverse learning style groups in group work, and explores how a grouping algorithm based on students' learning styles affects students' learning achievements and processes. An empirical study with current undergraduate students in the UK has been conducted. The participating students were invited to accomplish two group discussion tasks. Each student performed the two activities, in a separate group each time, once in a group consisting of students with similar learning styles, once in a group with diverse learning styles. No volunteer shared both groups with any individual student. This paper focuses on analysing the learning achievements and collaboration processes for the two types of groups, particularly with respect to the quality of group interactions. A significant difference was found between the percentages of time spent on meaningful interactions by the two types of groups, revealing that diverse learning style groups tend to spend significantly more time on meaningful interactions than similar learning style groups. In addition, the diverse learning style groups had demonstrated significantly less negative social-emotional reactions in showing disagreements.

Plagiarism is a growing problem in academia. Academics often use plagiarism detection tools to detect similar source-code files. Once similar files are detected, the academic proceeds with the investigation process which involves identifying the similar source-code fragments within them that could be used as evidence for proving plagiarism. This paper describes PlaGate, a novel tool that can be integrated with existing plagiarism detection tools to improve plagiarism detection performance. The tool also implements a new approach for investigating the similarity between source-code files with a view to gathering evidence for proving plagiarism. Graphical evidence is presented that allows for the investigation of source-code fragments with regards to their contribution toward evidence for proving plagiarism. The graphical evidence indicates the relative importance of the given source-code fragments across files in a corpus. This is done by using the Latent Semantic Analysis information retrieval technique to detect how important they are within the specific files under investigation in relation to other files in the corpus.

A nationwide sample of university students completed a survey that asked questions about their perceptions of the factors that can cause problems which exist with online or general group work. Data were obtained from 173 students at more than 18 different universities in the United Kingdom. Three main problems that exist in group collaboration are identified through an extensive review of literature and addressed as problem scenarios in the survey. These include: poor motivation, lack of individual accountability and negative interdependence. Findings from the survey include that on average more than five factors are acknowledged by the students for each subcategory of problem, and for each scenario the factors that affect the group work are ranked by importance level. Furthermore, we find no statistically significant association between the students' backgrounds and their perceptions of the factors identified.

A Pervasive Learning Space (PLS) uses context-awareness to link a virtual world with real world objects. We define viability as the extent to which a given PLS can be adapted to different purposes, and portability to be the extent to which a given PLS can be transferred to a new physical context. Heroes of Koskenniska is a game-based PLS combining mobile technology and a wireless sensor network in a forest context to raise the environmental awareness in a Biosphere Reserve in Finland. The game was built upon a screen-based architecture, and our analysis shows that it has higher portability and viability than a selection of related PLSs. The screen-based architecture is highly viable and portable because it is based on the model-view-controller division. Our preliminary observations indicate that the game helps to increase visitor count of the area and to promote interaction between visitors and nature.

One of the factors that affect successful collaborative learning is the composition of collaborative groups. Due to the lack of intelligent grouping according to learnerspsila pedagogic needs in current online collaborative learning environments, developing intelligent grouping according to individual learnerspsila cognitive characteristics is highly desired. In this paper, we propose a new approach to supporting intelligent grouping based on learnerspsila learning styles. Our approach achieves the balance of different levels of learning styles in group composition. We demonstrate how it can fit into current activity-based collaborative learning environments and how it could be applied in a real world application.

Using adaptive, personalized courses is rewarding, as it can create a better learning experience, tailored for a specific learner's needs. The process of creating these courses, however, is cumbersome and time consuming. Authors can be helped by employing automatization methods that relieve the authoring burden. We previously proposed a method which uses information from an author's Desktop to suggest extensions to existing courses. In this paper we report an experimental evaluation of the method, focusing on usability aspects.

Novice programmers require large amounts of time and motivation to learn an object-oriented programming language such as Java. In this paper, the architecture of our context-aware and adaptive learning schedule (CALS) tool is described. The tool has been designed to focus initially on supporting first year computer science undergraduate students to become more proficient Java programmers, and makes use of a learning schedule, where the learner inputs their daily activities. Based on this information, the tool is able to automatically determine the contextual features such as the location and available time. The appropriate learning materials are selected for the students according to, firstly, the learner preferences (such as learning styles), and secondly the contextual features (such as the level of concentration).

Few intelligent learning systems exist which are dynamic and able to provide personalized learning materials to satisfy individual students' requirements. We have developed an agent-based learning system that incorporates learning objects to facilitate personalization, and is based on a learning style theory as the pedagogic foundation for adaptivity. In this paper, we present our novel approach to the incorporation of learning style theory and learning objects, and evaluation indicates that the approach is able to provide personalized learning materials and improve the adaptivity in learning systems.

Computer programming lends itself to automated assessment. With appropriate software tools, program correctness can be measured, along with an indication of quality according to a set of metrics. Furthermore, the regularity of program code allows plagiarism detection to be an integral part of the tools that support assessment. In this paper, we describe a submission and assessment system, called BOSS, that supports coursework assessment through collecting submissions, performing automatic tests for correctness and quality, checking for plagiarism, and providing an interface for marking and delivering feedback. We describe how automated assessment is incorporated into BOSS such that it supports, rather than constrains, assessment. The pedagogic and administrative issues that are affected by the assessment process are also discussed.

The relative novelty of Educational Technology as a discipline yields challenges for the active researcher due to the interdisciplinary nature of the subject. We identify some of the issues which particularly affect doctoral students in educational technology and their supervisors.

The development of an online submission system at the authors' computer science department over the last few years is described. The changing technologies used by the in-house software are discussed, together with the pedagogic and administrative issues that are affected by the process. The authors conclude by examining the issues that currently direct the future development of the software.

Peer assessment is a technique that has been successfully employed in a variety of academic disciplines, and it is considered as effective in developing students' higher cognitive skills. This paper describes the potential for Web-based peer assessment with an anonymous communication tool, and reports the results of applying a novel Web-based technology to the delivery of peer assessment in the context of an undergraduate computer programming course.

Peer assessment is a technique that has been successfully employed in a variety of academic disciplines, and which is considered to be effective in developing student's higher cognitive skills. In this paper, we consider the results of applying novel web-based technology to the delivery of peer assessment in the context of an undergraduate computer programming course, and discuss the benefits of this approach.

With the increasing levels of access to higher education in the United Kingdom, larger class sizes make it unrealistic for tutors to be expected to identify instances of peer-to-peer plagiarism by eye and so automated solutions to the problem are required. This document details a novel algorithm for comparison of suspect documents at a sentence level and has been implemented as a component of plagiarism detection software for detecting similarities in both natural language documents and comments within program source-code. The algorithm is capable of detecting sophisticated obfuscation (such as paraphrasing, reordering, merging, and splitting sentences) as well as direct copying. The implemented algorithm has also been used to successfully detect plagiarism on real assignments at the university. The software has been evaluated by comparison with other plagiarism detection tools.

Peer assessment is a method of motivating students in learning computer programming, involving student's marking and providing feedback on other student's work. We report on the design and implementation of a novel Web-based peer assessment system, and discuss its deployment on a large programming module. The results indicate that this peer assessment system has successfully helped students to develop their understanding of computer programming.

We describe an initiative under way at Warwick to provide a technical foundation for computer-aided learning and computer-assisted assessment tools, which allows a rich dialogue sensitive to individual students' response patterns. The system distinguishes between dialogues for individual problems and the linking of problems. This enables a subject specialist to craft individual questions and units of learning material, while allowing the order of presentation of the units to depend on a student's interaction history. We develop a markup language, specified as an XML DTD, to enable the storage of data for use in such systems.

As student numbers on computer science courses continue to increase, the corresponding demands placed on teaching staff in terms of assessment grow ever stronger. In particular, the submission and assessment of practical work on large programming courses can present very significant problems. In response to this, we have developed a networked suite of software utilities that allow on-line submission, testing and marking of coursework. It has been developed and used over the course of five years, and has evolved into a mature tool that has greatly reduced the administrative time spent managing the processes of submission and assessment. In this paper, we describe the software and its implementation, and discuss the issues involved in its construction. Copyright © 1999 John Wiley & Sons, Ltd.

The Java Virtual Machine (JVM) was designed as the target for Java compilers, but there is no reason why it cannot be used as the target for other languages. We describe the implementation of a compiler which translates a lazy, weakly-typed functional program into Java class files. We compare the performance of our compiler to the only other known compiler from a lazy functional language to the JVM. The results are broadly similar, suggesting that to get a significant performance speed-up using this compilation paradigm will come only from increasing the performance of the JVM, rather than enhancing the compiler itself. Copyright © 1999 John Wiley & Sons, Ltd.

In response to the demands of increasing student numbers, the BOSS system for submission and assessment has been constructed to enable student programming assignments to be submitted and tested on-line. More recent developments of this system have been concerned with the addition of electronic marking facilities that incorporate both automated marking, resulting from the automated testing, and manual marking in a secure environment. This paper briefly reviews the system and describes in detail the electronic marksheets, their functionality, and their user-interface.

In this paper we aim to give an introduction to fuzzy logic using the language Haskell to implement our solutions. We shall see how the high-level, declarative nature of a functional language allows us to implement easily and efficiently solutions to problems using fuzzy logic and, in particular, how the presence of functions as first-class values allows us to model the key concept of the fuzzy subset in a natural way.