The effects of gender on the transition of transfer students into a new school

The present study describes a peer-tutoring program designed to utilize computerassisted instruction to help first through fourth graders who were entering a new school. Tutored girls increased their positive self-perceptions as a result of the tutoring program, whereas boys declined in positive self-perceptions, while exhibiting gains in reading scores. These findings suggest that prevention efforts need to consider the specific adaptation needs of transfer students by gender so as to insure a maximum fit between individual need and program scope.     

The Critical Role of Stereopsis in Virtual and Mixed Reality Learning Environments

Anatomy education has been revolutionized through digital media, resulting in major advances in realism, portability, scalability, and user satisfaction. However, while such approaches may well be more portable, realistic, or satisfying than traditional photographic presentations, it is less clear that they have any superiority in terms of student learning. In this study, it was hypothesized that virtual and mixed reality presentations of pelvic anatomy will have an advantage over two-dimensional (2D) presentations and perform approximately equal to physical models and that this advantage over 2D presentations will be reduced when stereopsis is decreased by covering the non-dominant eye. Groups of 20 undergraduate students learned pelvic anatomy under seven conditions: physical model with and without stereo vision, mixed reality with and without stereo vision, virtual reality with and without stereo vision, and key views on a computer monitor. All were tested with a cadaveric pelvis and a 15-item, short-answer recognition test. Compared to the key views, the physical model had a 70% increase in accuracy in structure identification; the virtual reality a 25% increase, and the mixed reality a non-significant 2.5% change. Blocking stereopsis reduced performance on the physical model by 15%, on virtual reality by 60%, but by only 2.5% on the mixed reality technology. The data show that virtual and mixed reality technologies tested are inferior to physical models and that true stereopsis is critical in learning anatomy.     

Automating the Construction of Internet Portals with Machine Learning

Domain-specific internet portals are growing in popularity because they gather content from the Web and organize it for easy access, retrieval and search. For example, www.campsearch.com allows complex queries by age, location, cost and specialty over summer camps. This functionality is not possible with general, Web-wide search engines. Unfortunately these portals are difficult and time-consuming to maintain. This paper advocates the use of machine learning techniques to greatly automate the creation and maintenance of domain-specific Internet portals. We describe new research in reinforcement learning, information extraction and text classification that enables efficient spidering, the identification of informative text segments, and the population of topic hierarchies. Using these techniques, we have built a demonstration system: a portal for computer science research papers. It already contains over 50,000 papers and is publicly available at www.cora.justresearch.com. These techniques are widely applicable to portal creation in other domains.     

Estimation and reliability of retrieval effectiveness measures

A probabilistic model of the retrieval process is presented. From it, the standard errors of system recall and precision estimators, based on a sample of queries, are derived. The resulting negative binomial model is fitted to empirical data from several retrieval tests.     

Stability of Attachment Style in Adolescence: An Empirical Test of Alternative Developmental Processes

Few studies have examined stability and change in attachment during adolescence. This 5‐year longitudinal study (a) examined whether prototype or revisionist developmental dynamics better characterized patterns of stability and change in adolescent attachment (at T1, N = 176; M_age = 14.0 years, SD = 0.9), (b) tested potential moderators of prototype‐like attachment stability, and (c) compared attachment stability in adolescence to stability in adulthood. The results supported the prototype model, which assumes that there is a stable, enduring factor underlying stability and change in attachment. Exploratory moderation analyses revealed that family conflict, parental separation or divorce, minority status, and male sex might undermine the prototype‐like stability of adolescent attachment. Stability of attachment was lower in adolescence relative to adulthood.     

A machine learning approach to investigating the effects of mathematics dispositions on mathematical literacy

Mathematics competency is fast becoming an essential requirement in ever greater parts of day-to-day work and life. Thus, creating strategies for improving mathematics learning in students is a major goal of education research. However, doing so requires an ability to look at many aspects of mathematics learning, such as demographics and psychological dispositions, in an integrated way as part of the same system. Large-scale assessments such as the Programme for International Student Assessment (PISA) provide an accessible and large volume of coherent data, and this gives researchers the opportunity to employ data-driven approaches to gain an overview of the system. For these reasons, we have used machine learning to explore the relationships between psychological dispositions and mathematical literacy in Australian 15-year-olds using the PISA 2012 data set. Our results from this strongly data-driven approach re-affirm the primacy of mathematics self-efficacy and highlight novel complex interactions between mathematics self-efficacy, mathematics anxiety and socio-economic status. In this paper, we demonstrate how education researchers can usefully employ data-driven modelling techniques to find complex non-linear relationships and novel interactions in a multidimensional data set.     

Aesthetics and credibility in web site design

Web sites often provide the first impression of an organization. For many organizations, web sites are crucial to ensure sales or to procure services within. When a person opens a web site, the first impression is probably made in a few seconds, and the user will either stay or move on to the next site on the basis of many factors. One of the factors that may influence users to stay or go is the page aesthetics. Another reason may involve a user’s judgment about the site’s credibility. This study explores the possible link between page aesthetics and a user’s judgment of the site’s credibility. Our findings indicate that when the same content is presented using different levels of aesthetic treatment, the content with a higher aesthetic treatment was judged as having higher credibility. We call this the amelioration effect of visual design and aesthetics on content credibility. Our study suggests that this effect is operational within the first few seconds in which a user views a web page. Given the same content, a higher aesthetic treatment will increase perceived credibility.     

Using importance‐performance analysis to evaluate training

The importance‐performance analysis (IPA) is a tool that can provide timely and usable feedback to improve training. IPA measures the gaps between the importance and how “good” (performance) a class is perceived by a student and is presented on a 2x2 matrix. The quadrant in which data land in this matrix aids in determining potential future action. This article focuses on integrating IPA into Kirkpatrick's (1959) four‐level framework of evaluation. Examples and suggestions for improving training are discussed.