Feedback seeking behaviour in higher education: the association with students’ goal orientation and deep learning approach

To make sure that feedback fulfils its aspirations, students’ active role in feedback should be acknowledged in higher education: It is students’ uptake of feedback that determines its effectiveness. In this study, feedback seeking behaviour of students is introduced in order to enrich our knowledge about students’ active role in feedback. Goal orientation was studied as antecedent of feedback seeking behaviour, and students’ deep learning approach as a mediating factor. Results indicated that students use both monitoring and inquiry strategies of feedback seeking, but they preferred monitoring. The association between feedback seeking behaviour and goal orientation was stronger for mastery goals than for performance goals. The preference for monitoring is stronger for students with more performance goal orientation. Deep learning approach was found to be a mediator in the relationship between goal orientation and feedback seeking behaviour. It can be concluded that students with the goal to learn from the activity will use more deep learning strategies and will seek more feedback, both in an active and passive way. This effect is less present for students with performance goals.     

Historical Networks in Science Education

Science & Education - This paper discusses the potential of the creation and analysis of historical networks as didactic strategies in science education. To this end, we first argue the...     

Progress to conservation: Conflict or correct answer?

One of the fundamental problems in socio-cognitive conflict theory concerns what it is that leads to cognitive growth. Is it conflict per se, i.e. the fact that two contradictory opinions are brought together, or is it the presence of the correct answer which is essential for growth. In this experiment, dyads, functioning on the same cognitive level, were formed and asked to solve a conservation-of-length task. The classification of the children in the pre-test was not done according to Piagetian norms, but according to Flavell’s appearance-reality (AR) model: AR non-conservers (AR-NC), AR intermediates (AR-I) and AR conservers (AR-C). Many children who would have been scored as non-conservers in a standard Piagetian task, showed an underlying conservation competence and were classified as AR-I. The results of the interaction suggest that conflict does not lead to appropriate change in AR-NC dyads or AR-I dyads. Furthermore, the results suggest that the most effective method for AR-I to become conservers, is to make them think about a problem and then, to create consensus by confronting the children with others who have also reached the correct solution.     

Object-naming deficits in developmental dyslexia

This paper reports two experiments which focus on the object naming deficits of dyslexic readers. In Experiment 1, dyslexic and normal readers were asked to name objects depicted by pictures or following their spoken definition. Ten-year-old dyslexics named fewer objects correctly than other children of a similar age, performing only as well as a younger group of 8-year-old normal readers. This was true irrespective of the modality through which they were tested. In terms of naming latency, however, they were similar to comparison groups. In Experiment 2, nine-year-old dyslexic and normal readers performed as well as each other in a receptive vocabulary test in which pictures had to be matched to spoken words. However, once again, on a picture naming test, the dyslexics did less well than controls. We argue that dyslexic children are subject to verbal naming difficulties which cannot be accounted for by generally low levels of vocabulary knowledge. Their problems are attributable not to difficulties in semantic representation but to difficulties with the lexical-phonological representation of spoken words they know. We propose that, in turn, these difficulties are related to their memory and reading problems.     

Latent Markov Factor Analysis for Exploring Measurement Model Changes in Time-Intensive Longitudinal Studies

When time-intensive longitudinal data are used to study daily-life dynamics of psychological constructs (e.g., well-being) within persons over time (e.g., by means of experience sampling methodology), the measurement model (MM)—indicating which constructs are measured by which items—can be affected by time- or situation-specific artifacts (e.g., response styles and altered item interpretation). If not captured, these changes might lead to invalid inferences about the constructs. Existing methodology can only test for a priori hypotheses on MM changes, which are often absent or incomplete. Therefore, we present the exploratory method “latent Markov factor analysis” (LMFA), wherein a latent Markov chain captures MM changes by clustering observations per subject into a few states. Specifically, each state gathers validly comparable observations, and state-specific factor analyses reveal what the MMs look like. LMFA performs well in recovering parameters under a wide range of simulated conditions, and its empirical value is illustrated with an example.     

Impact of the Good Behavior Game on special education teachers

This study tested effects of a program that offers teachers universal classroom management strategies, on teachers’ burnout symptoms and self-efficacy, and their teaching behaviors. Data were collected from 147 teachers (mean age = 38.4 years, SD = 10.8) in 15 special secondary education schools for students with emotional and behavioral problems, at the start and end of the school year. Schools were randomly assigned to the experimental condition or a care-as-usual condition. Results show that the program impacted beneficially on self-reported levels of emotional exhaustion, and self-efficacy in engaging students and in classroom management, but not on teaching behaviors. Implications of this study for the professional development of teachers in special education and research are discussed.     

The Influence of Career Beliefs and Socio-Economic Status on the Career Decision-Making of High School Students in India

This paper responds to current discussions in career psychology that emphasise the importance of understanding how socio-economic backgrounds and social-cognitive environments influence career development. Located in India, this study examines the interaction between career beliefs and socio-economic status within a sample of Indian high school students. Significant socio-economic status differences were observed, with the lower SES groups showing higher levels of negative career beliefs. The relevance of these findings to career psychologists who work in multi cultural contexts is discussed within the framework of the Social Cognitive Theories of Career Decision Making. This revised version was published online in July 2006 with corrections to the Cover Date.     

Didactic and technical considerations when developing e-learning and CME

Several usability issues were encountered during the design of a blended e-learning program for a course in evidence-based medicine for general practice trainers. The program was developed in four steps. We focused in this article on step 2 and 3. Step 2 focused on which educational principles to apply, that is, which learning theories, instructional designs and other theories should influence the program. Step 3 focused on the design elements, namely whether to use hypermedia and/or multimedia, and what screen design and which font to use. This article presents the important issues in designing an e-course and provides an impression of the complexity of designing high quality e-learning in particular for continuing medical education (CME).