Facebook & Blackboard: comparison of learner perspectives

Different systems, different purposes – but how do they compare as learning environments? We undertook a survey of students at the University, asking whether they learned from their use of the systems, whether they made contact with other students through them, and how often they used them. Although it was a small scale survey, the results are quite enlightening and quite surprising. Blackboard is populated with learning material, has all the students on a module signed up to it, a safe environment (in terms of Acceptable Use and some degree of staff monitoring) and provides privacy within the learning group (plus lecturer and relevant support staff). Facebook, on the other hand, has no learning material, only some of the students using the system, and on the face of it, it has the opportunity for slips in privacy and potential bullying because the Acceptable Use policy is more lax than an institutional one, and breaches must be dealt with on an exception basis, when reported. So why do more students find people on their courses through Facebook than Blackboard? And why are up to 50% of students reporting that they have learned from using Facebook? Interviews indicate that students in subjects which use seminars are using Facebook to facilitate working groups – they can set up private groups which give them privacy to discuss ideas in an environment which perceived as safer than Blackboard can provide. No staff interference, unless they choose to invite them in, and the opportunity to select who in the class can engage. The other striking finding is the difference in use between the genders. Males are using blackboard more frequently than females, whilst the reverse is true for Facebook. Interviews suggest that this may have something to do with needing to access lecture notes… Overall, though, it appears that there is little relationship between the time spent engaging with Blackboard and reports that students have learned from it. Because Blackboard is our central repository for notes, any contact is likely to result in some learning. Facebook, however, shows a clear relationship between frequency of use and perception of learning – and our students post frequently to Facebook. Whilst much of this is probably trivia and social chit chat, the educational elements of it are, de facto, contructivist in nature. Further questions need to be answered - Is the reason the students learn from Facebook because they are creating content which others will see and comment on? Is it because they can engage in a dialogue, without the risk of interruption by others?

Learner strategies and self-efficacy: making the connection

This article reports on part of a larger study of the impact of strategy training in listening on learners of French, aged 16 to 17. One aim of the project was to investigate whether such training might have a positive effect on the self-efficacy of learners, by helping them see the relationship between the strategies they employed and what they achieved. One group of learners, as well as receiving strategy training, also received detailed feedback on their listening strategy use and on the reflective diaries they were asked to keep, in order to draw their attention to the relationship between strategies and learning outcomes. Another group received strategy training without feedback or reflective diaries, while a comparison group received neither strategy training nor feedback. As a result of the training, there was some evidence that students who had received feedback had made the biggest gains in certain aspects of self-efficacy for listening; although their gains as compared to the non-feedback group were not as great as had been anticipated. Reasons for this are discussed. The article concludes by suggesting changes in how teachers approach listening comprehension that may improve learners' view of themselves as listeners.

Intelligent cores and intelligent agents: two approaches to achieve autonomy in swarm-array computing

How can a bridge be built between autonomic computing approaches and parallel computing systems? How can autonomic computing approaches be extended towards building reliable systems? How can existing technologies be merged to provide a solution for self-managing systems? The work reported in this paper aims to answer these questions by proposing Swarm-Array Computing, a novel technique inspired from swarm robotics and built on the foundations of autonomic and parallel computing paradigms. Two approaches based on intelligent cores and intelligent agents are proposed to achieve autonomy in parallel computing systems. The feasibility of the proposed approaches is validated on a multi-agent simulator.

Factors mediating the routinisation of e-learning within a traditional university education environment

Technology-enhanced or Computer Aided Learning (e-learning) can be institutionally integrated and supported by learning management systems or Virtual Learning Environments (VLEs) to offer efficiency gains, effectiveness and scalability of the e-leaning paradigm. However this can only be achieved through integration of pedagogically intelligent approaches and lesson preparation tools environment and VLE that is well accepted by both the students and teachers. This paper critically explores some of the issues relevant to scalable routinisation of e-learning at the tertiary level, typically first year university undergraduates, with the teaching of Relational Data Analysis (RDA), as supported by multimedia authoring, as a case study. The paper concludes that blended learning approaches which balance the deployment of e-learning with other modalities of learning delivery such as instructor–mediated group learning etc offer the most flexible and scalable route to e-learning but that this requires the graceful integration of platforms for multimedia production, distribution and delivery through advanced interactive spaces that provoke learner engagement and promote learning autonomy and group learning facilitated by a cooperative-creative learning environment that remains open to personal exploration of constructivist-constructionist pathways to learning.

Analysing lexical richness in French learner language: what frequency lists and teacher judgements can tell us about basic and advanced words

We show how teacher judgements can be used to assess the quality of vocabulary used by L2 learners of French.

Do national cultural differences affect the nature and characteristics of HRM practices? Evidence from Australian and Hong Kong construction firms on remuneration and job autonomy

Human resource management (HRM) plays a pivotal role in attracting and retaining talents. However, there is growing recognition in international HRM literature that the adoption of the widely accepted US/Harvard-inspired HRM model ignores the influences of cultural contexts on HRM practices in different countries. This notion has not been empirically investigated in the construction industry. Based on survey responses from 604 construction professionals from Australia and Hong Kong, this study examines whether: (i) national cultural differences influence individuals’ preference for types of remuneration and job autonomy, (ii) actual organizational HRM practices reflect such preferences and (iii) gaps between individuals’ preferences and actual organizational HRM practices affect job satisfaction. Results showed significant difference in HRM preferences between Australian and Hong Kong respondents and these are reflected in the distinct types of HRM practices adopted by construction firms in the two countries. Findings further indicated that the gap between individuals’ preferences and actual organizational HRM practices is associated with job satisfaction. The results support existing mainstream research and highlight the deficiency of the acultural treatment of HRM that is still apparent in construction management literature. An uncritical literature in the area not only hinders theory development but also potentially undermines the ability of construction firms to attract, recruit, and retain scarce talents.

Parallel random prism: a computationally efficient ensemble learner for classification

Generally classifiers tend to overfit if there is noise in the training data or there are missing values. Ensemble learning methods are often used to improve a classifier's classification accuracy. Most ensemble learning approaches aim to improve the classification accuracy of decision trees. However, alternative classifiers to decision trees exist. The recently developed Random Prism ensemble learner for classification aims to improve an alternative classification rule induction approach, the Prism family of algorithms, which addresses some of the limitations of decision trees. However, Random Prism suffers like any ensemble learner from a high computational overhead due to replication of the data and the induction of multiple base classifiers. Hence even modest sized datasets may impose a computational challenge to ensemble learners such as Random Prism. Parallelism is often used to scale up algorithms to deal with large datasets. This paper investigates parallelisation for Random Prism, implements a prototype and evaluates it empirically using a Hadoop computing cluster.