Robotics,an academic discipline?

Robotics is currently an ad hoc collection of topics spread through a number of disciplines. The knowledge explosion that has occurred in robotics, during the first half of the 1980s, raises the question: ‘Should robotics become a separate discipline?’ To become a discipline in its own right, the various topics in robotics have to be combined into a unified body of knowledge, clear definitions of the terms robot and robotics have to be agreed upon, and a set of axioms formulated. If this can be done then a paradigm for robotics research can be established, as well as a set of goals.Each of these issues is addressed, and definitions are formulated. The content of the discipline is described within the framework of a proposed university curriculum. This curriculum demonstrates that there is a cohesive body of knowledge which constitutes the field of robotics. From the quantity and quality of the content of the curriculum we can see that the discipline is potentially large, and is based upon solid theoretical grounds. There is potential for robotics to emerge as a separate academic discipline within the next decade.     

What is the academic efficacy of podcasting?

Podcasting may be an answer to some of the challenges to higher education to modernize, to open up, and to develop a competitive edge. However, over the years there have been many high claims for new technology, and not all of them have been redeemed. In terms of academic performance, it may therefore be asked if podcasting really is worth the investment? Looking for at least a tentative answer, the present paper reviews an extensive body of scholarly literature published 2004–2009 on experiences with podcasting in higher education.     

Individuality or conformity? Identity in personal and university academic homepages

The connection between writing and identity has been a subject of academic interest for some time and there is now broad agreement that identity is created from the texts we engage in and the semiotic choices we make. In this view, the process of constructing an identity most clearly involves selecting materials to present to others, a process which is seen most directly in personal homepages. It has become almost obligatory for academics to maintain some kind of online presence, although these homepages can also serve the university in several ways and therefore suppresses more personal facets of identity and act to position the author as an employee. As a result, many academics seek to escape the bland uniformity of the university personal page to present a more multi-faceted identity in a self-managed homepage. This paper explores the this relatively neglected area of composition to show how identity is discursively constructed in a corpus of 100 homepages of 50 academics, one university-managed and the other personally created. Focusing on textual content, design, links and photographs, I contrast some of the ways that academics elect to represent themselves as academics in these two environments.     

How does the smartphone usage of college students affect academic performance?

The present study aims to investigate the effects of smartphone use by college students on their perceived academic performance. Using five hypotheses derived from the literature related to smartphone use, the initial model was set up for path analysis to reveal the relationships among variables regarding college students' smartphone use in the academic setting. Moreover, multiple group analyses were additionally conducted to verify whether students exhibited different relationships in the hypothesized model depending on their majors. The results from path analyses showed that all path coefficients were positive and statistically significant, which indicated that all five hypothesized paths were supported. Above all, the results from multiple group analysis showed that one path (from Behavioural Intention to Use Smartphone to Academic Performance) differed significantly across groups. The findings from the current study provide educational policymakers and educators with information on how smartphone utilization in learning activities influences students' academic performance.     

Finding academic experts on a multisensor approach using Shannon’s entropy

Expert finding is an information retrieval task concerned with the search for the most knowledgeable people, in some topic, with basis on documents describing peoples activities. The task involves taking a user query as input and returning a list of people sorted by their level of expertise regarding the user query. This paper introduces a novel approach for combining multiple estimators of expertise based on a multisensor data fusion framework together with the Dempster–Shafer theory of evidence and Shannon’s entropy. More specifically, we defined three sensors which detect heterogeneous information derived from the textual contents, from the graph structure of the citation patterns for the community of experts, and from profile information about the academic experts. Given the evidences collected, each sensor may define different candidates as experts and consequently do not agree in a final ranking decision. To deal with these conflicts, we applied the Dempster–Shafer theory of evidence combined with Shannon’s Entropy formula to fuse this information and come up with a more accurate and reliable final ranking list. Experiments made over two datasets of academic publications from the Computer Science domain attest for the adequacy of the proposed approach over the traditional state of the art approaches. We also made experiments against representative supervised state of the art algorithms. Results revealed that the proposed method achieved a similar performance when compared to these supervised techniques, confirming the capabilities of the proposed framework.     

How influential has academic and industrial research been in current software life cycles? A retrospective analysis of four mainstream activities

ContextKnowledge transfer is an important responsibility of universities and research institutes as part of their contribution to society. In the field of software engineering, several studies have been performed to show the influence of research in popular technologies such as middleware systems. However, there is no scholarly analysis of the influence that research has had in mainstream activities of current software life cycles.ObjectiveWe analyse how methodological research has influenced activities of widespread use in current software life cycles. To keep this goal into manageable bounds, we focus on four very successful trends of current practice: iterative development, architecture-centric development, requirements-driven development, and coherent method integration.MethodWe follow different forms of evidence backwards in time. As signs of influence we admit the following categories: citations included in papers and standards, interviews, historical essays, people movement, and acquisitions of companies.ResultsFor each one of the mentioned activities, we obtain a trace diagram showing the indirect influence that pieces of research have had in the selected activities of software life cycles.ConclusionsOur results support the following claims: (1) mainstream dissemination of the analysed methodological research has taken on the order of 20–40 years; (2) interdisciplinarity has been important in the research that influenced some very popular activities of current software life cycles; (3) research on life cycles is more influential when it originates from large development projects; and (4) probably the best results can be obtained if industrial research goes hand in hand with academic research.     

Patterns of students' collaborations by variations in their learning orientations in blended course designs: How is it associated with academic achievement?

Background

While a number of learner factors have been identified to impact students' collaborative learning, there has been little systematic research into how patterns of students' collaborative learning may differ by their learning orientations.

Objectives

This study aimed to investigate: (1) variations in students' learning orientations by their conceptions, approaches, and perceptions; (2) the patterns of students' collaborations by variations in their learning orientations and (3) the contribution of patterns of collaborations to academic achievement.

Methods

A cohort of 174 Chinese undergraduates in a blended engineering course were surveyed for their conceptions of learning, approaches to learning and to using online learning technologies, and perceptions of e-learning, to identify variations in their learning orientations. Students' collaborations and mode of collaborations were collected through an open-ended social network analysis (SNA) questionnaire.

Results and Conclusions

A hierarchical cluster analysis identified an ‘understanding’ and ‘reproducing’ learning orientations. Based on students' learning orientations and their choices to collaborate, students were categorized into three mutually exclusive collaborative group, namely Understanding Collaborative group, Reproducing Collaborative group and Mixed Collaborative group. SNA centrality measures demonstrated that students in the Understanding Collaborative group had more collaborations and stayed in a better position in terms of capacity to gather information. Both students' approaches to learning and students' average collaborations significantly contributed to their academic achievement, explaining 3% and 4% of variance in their academic achievement respectively. The results suggest that fostering a desirable learning orientation may help improve students' collaborative learning.     

Modelling the dynamics of the students’ academic performance in the German region of the North Rhine-Westphalia: an epidemiological approach with uncertainty

Student academic underachievement is a concern of paramount importance in Europe, where around 15% of the students in the last high school courses do not achieve the minimum knowledge academic requirement. In this paper, we propose a model based on a system of differential equations to study the dynamics of the students’ academic performance in the German region of the North Rhine-Westphalia. This approach is supported by the idea that both good and bad study habits, are a mixture of personal decisions and influence of classmates. This model allows us to forecast the student academic performance by means of confidence intervals over the next few years.     

Students' self-report and observed learning orientations in blended university course design: How are they related to each other and to academic performance?

This study examines the extent to which the learning orientations identified by student self-reports and the observation of their online learning events were related to each other and to their academic performance. The participants were 322 first-year engineering undergraduates, who were enrolled in a blended course. Using students' self-report on a questionnaire about their approaches to learning and perceptions of the blended learning environment, ‘understanding’ and ‘reproducing’ learning orientations were identified. Using observations of student activity online, a Hidden Markov Model (HMM) and agglomerative sequence clustering detected four qualitatively different patterns of online learning orientations. Cross-tabulations showed significant and logical associations amongst the learning orientations derived by the self-report and observational methods. Significant differences were also consistently found in the students' academic performance across the mid-term and final assessments based on their learning orientations detected by both self-report and observational methods, results which have important implications for learning research.     

To Facebook or to Face Book? An investigation of how academic performance of different personalities is affected through the intervention of Facebook usage

This paper investigates how students’ personality types influence their academic performance and how Facebook usage intervenes these associations. A survey questionnaire method was adopted to collect data from students in five public universities in Malaysia. An analysis of 1165 questionnaires shows that all five dimensions of personality from big five model predict academic performance. In addition, shyness also predicted academic performance positively while a negative relationship was found between loneliness and students’ academic performance. The mediating role of Facebook usage was established only in the relationships of academic performance with extraversion, agreeableness and loneliness. A discussion of these findings, limitations of the study and future research directions are provided.