This study examined how desktop virtual reality (VR) enhances learning and not merely does desktop VR influence learning. Various relevant constructs and their measurement factors were identified to examine how desktop VR enhances learning and the fit of the hypothesized model was analyzed using structural equation modeling. The results supported the indirect effect of VR features to the learni...

The competition fostered in today's environment is demanding increased accountability of collegiate instructors and re-evaluation of traditional teaching methods. Without reliable and valid instructional measurement systems, it is virtually impossible to benchmark new techniques or identify effective instructors. In addition, these measures need to be comprehensive. This research describes the ...

Relevance and diversity are both crucial criteria for an effective search system. In this paper, we propose a unified learning framework for simultaneously optimizing both relevance and diversity. Specifically, the problem is formalized as a structural learning framework optimizing DiversityCorrelated Evaluation Measures (DCEM), such as ERR-IA, α-NDCG and NRBP. Within this framework, the discri...

In categorial systems with a fixed structural component, the learning problem comes down to finding the solution for a set of typeassignment equations. A hard-wired structural component is problematic if one want to address issues of structural variation. Our starting point is a type-logical architecture with separate modules for the logical and the structural components of the computational sy...

the main objective of this descriptive- suvey research was to analyze components of quality of e-learning in the iranian agricultural higher education. the statistical population of the study consisted of the graduate students of iranian agricultural colleges (n=8541), out of which 286 people determined as sample using cochran formula and proportionate stratified sampling technique. the data we...

It is well known that individual learning can speed up arti cial evo lution enormously However both supervised learning and reinforcement learning require speci c learning goals which usually are not available or di cult to nd We introduce a new principle homeokinesis which is completely unspeci c and yet induces speci c seemingly goal oriented behaviors of an agent in a complex external world ...

Tree induction algorithms use heuristic information to obtain decision tree classification. However, there has been little research on how many rules are appropriate for a given set of data, that is, how we can find the best structure leading to desirable generalization performance. In this chapter, an evolutionary multi-objective optimization approach with genetic programming will be applied t...

The Iowa Gambling Task (IGT) is assumed to measure executive functioning, but this has not been empirically tested by means of both convergent and discriminant validity. We used structural equation modeling (SEM) to test whether the IGT is an executive function (EF) task (convergent validity) and whether it is not related to other neuropsychological domains (discriminant validity). Healthy comm...