Functionalizing human relations in business

This commentary argues that Indvik and Fitzpatrick's article, “Perceptions of Inclusion, Affiliation, and Control in Five Interpersonal Relationships,” presents an inappropriate conceptual and methodological approach to the study of relationship defining communication. Problems are most evident in: (1) the domain isolated to represent the themes of inclusion, control, and affection; and (2) the inattention to the interdependence established with communication between relationship partners.     

Un profil de compétences pour les professeurs d’informatique de l’enseignement secondaire camerounais

A competency profile for teachers of Computer Science in Cameroonian secondary education – In 1998, the Cameroonian government decided to introduce Computer Science as a school subject. To implement this decision, it began to train teachers of Computer Science according to the same training model used for teachers of other disciplines. Despite the consensus that seems to be emerging from the scientific community regarding the need to give priority to a cross-disciplinary use of information and communication technologies (ICT) in primary and secondary education, some countries, such as Cameroon, have opted to teach Computer Science. While such a political choice might in principle appear to be inappropriate for the development of students’ ICT skills, the article shows that it nevertheless introduces teachers into the system who have a predisposition to act as catalysts for the pedagogical integration of ICT. Such a development could occur provided these teachers are trained in a range of additional skills – those proposed in the article – which would enable them to contribute effectively. If this approach were implemented, sub-Saharan countries such as Cameroon would, in their Computer Science teachers, have access to human resources capable of quickly generalising the cross-disciplinary use of ICT in the education system.     

The Crux of Crucial Experiments: Duhem's Problems and Inference to the Best Explanation

Going back at least to Duhem, there is a tradition of thinkingthat crucial experiments are impossible in science. I analyseDuhem's arguments and show that they are based on the excessivelystrong assumption that only deductive reasoning is permissiblein experimental science. This opens the possibility that someprinciple of inductive inference could provide a sufficientreason for preferring one among a group of hypotheses on thebasis of an appropriately controlled experiment. To be sure,there are analogues to Duhem's problems that pertain to inductiveinference. Using a famous experiment from the history of molecularbiology as an example, I show that an experimentalist versionof inference to the best explanation (IBE) does a better jobin handling these problems than other accounts of scientificinference. Furthermore, I introduce a concept of experimentalmechanism and show that it can guide inferences from data withinan IBE-based framework for induction.

1. Introduction
2. Duhem onthe Logic of Crucial Experiments
3. ‘The Most BeautifulExperiment in Biology’
4. Why Not Simple Elimination?
5. SevereTesting
6. An Experimentalist Version of IBE

   6.1 Physiologicaland experimentalmechanisms

   6.2 Explaining the data

   6.3IBE and the problemof untested auxiliaries

   6.4 IBE-turtlesall the way down

7. Van Fraassen's ‘Bad Lot’ Argument
8. IBE and Bayesianism
9. Conclusions

     

How to evaluate rankings of academic entities using test data

In the field of scientometrics, impact indicators and ranking algorithms are frequently evaluated using unlabelled test data comprising relevant entities (e.g., papers, authors, or institutions) that are considered important. The rationale is that the higher some algorithm ranks these entities, the better its performance. To compute a performance score for an algorithm, an evaluation measure is required to translate the rank distribution of the relevant entities into a single-value performance score. Until recently, it was simply assumed that taking the average rank (of the relevant entities) is an appropriate evaluation measure when comparing ranking algorithms or fine-tuning algorithm parameters.With this paper we propose a framework for evaluating the evaluation measures themselves. Using this framework the following questions can now be answered: (1) which evaluation measure should be chosen for an experiment, and (2) given an evaluation measure and corresponding performance scores for the algorithms under investigation, how significant are the observed performance differences?Using two publication databases and four test data sets we demonstrate the functionality of the framework and analyse the stability and discriminative power of the most common information retrieval evaluation measures. We find that there is no clear winner and that the performance of the evaluation measures is highly dependent on the underlying data. Our results show that the average rank is indeed an adequate and stable measure. However, we also show that relatively large performance differences are required to confidently determine if one ranking algorithm is significantly superior to another. Lastly, we list alternative measures that also yield stable results and highlight measures that should not be used in this context.     

Exploring Self-Efficacy among Entry-Level and Advanced BSW Students

This study compared a sample of entry-level and advanced BSW students, who completed pretest and posttest self-efficacy measures, to assess their level of confidence in performing social work tasks after 15 weeks of instruction. By the end of the semester, only advanced students made significant gains in self-efficacy beliefs, and they showed a significantly higher self-efficacy belief than entry-level students. Results suggest that increased mastery experiences, as found in the advanced social work curriculum, may help students develop confidence in their ability to practice as professional social workers.     

Peer partnership to enhance scholarship of teaching: a case study

This paper reports on the outcomes of a peer partnership program trialled at the Queensland University of Technology (QUT), Australia. The program was designed based on a community of practice methodology to bring together academic staff for the purpose of advancing teaching practice. The program encouraged professional and supportive environments for the purpose of critical reflection and personal development. The belief was that quality teaching is core business and vital to university organisational goals. Peer partnership programs support improvement in teaching and learning. Participants in the program reported the program enhanced their commitment and insight into teaching and that there is willingness to be involved if supported by colleagues and an organisation. Feedback from participants in the program was positive and outcomes arising from the QUT Peer Partnership Project were the development of an online peer partner tool-kit, staff development training, an instructional DVD and integration of the project goals within QUT staff development programs.