The main goal of this research is to enhance the understanding of quality criteria for DB metadata for assessment and recognition as factors increasing their value in higher education (HE). To attain this goal, a case study approach centered in one HE institution was used, aiming (a) at an analysis of the status quo description of metadata of DBs issued by the HE institution to identify the value of DBs in terms of assessment and recognition procedures, and (b) a list of quality criteria for DB description metadata was proposed on the basis of academic research and on expert interview results. The results of the research demonstrate that in the institution under research, these criteria are not present in most cases of DB descriptions as teachers do not provide them. Distinct assessment and recognition criteria make an important quality factor for the DBs to become valid and valued digital credentials in HE.
In this study we investigate the effects of long-term technology enhanced learning (TEL) in mathematics learning performance and fluency, and how technology enhanced learning can be integrated into regular curriculum. The study was conducted in five second grade classes. Two of the classes formed a treatment group and the remaining three formed a control group. The treatment group used TEL in one mathematics lesson per week for 18 to 24 months. Other lessons were not changed. The difference in learning performance between the groups tested using a post-test; for that, we used a mathematics performance test and a mathematics fluency test. The results showed that the treatment group using TEL got statistically significantly higher learning performance results compared to the control group. The difference in arithmetic fluency was not statistically significant even though there was a small difference in favor of the treatment group. However, the difference in errors made in the fluency test was statistically significant in favor of the treatment group.
Learning Object (LO) is one of the main research topics in the e-learning community in the recent years. In this context, granularity is a key factor for LO reuse. This paper presents a methodology to define the learning objects granularity in the computing area as well as a case study in software testing. We carried out five experiments to evaluate the learning potential from the produced learning objects, as well as to demonstrate the possibility of LO reuse. The results show that LOs promote the understanding and application of the concepts. In addition, the set of LOs identified through the proposed methodology allowed its reuse in different contexts.
A brief overview of formation method of flexible learning objects is presented in this article. The basis of this method is e-learning material that is structured and separated from display rules. The learning objects that have such e-learning material may be adapted to individual needs and may be used in different learning contexts without changing e-learning material. To change the presentation form of e-learning material of such objects, it is enough to change display rules of this material. However, if the e-learning material must be adapted too, it is much easier to do this as the material is structured and contains less technical information of representation. The adaptation of such learning objects is more effective and needs less work time input, therefore they are called as flexible learning objects.