0000000000007624
AUTHOR
Vija Vagale
Uz lietotāja modeli balstīta personalizēta adaptīva e-studiju sistēma
Promocijas darbs ir veltīts uz lietotāja modeli balstītas personalizētas adaptīvas e-studiju sistēmas izveides metožu izstrādei, lai veicinātu un uzlabotu e-studiju izmantošanu apmācības procesā. Darbā apskatīti adaptīvajās sistēmās iekļaujamie pamatmodeļi, īpašu uzmanību veltot lietotāja modelim un eksistējošajām adaptācijas metodēm. Balstoties uz esošo risinājumu analīzi, ir izstrādāts uz datu dzīves ilgumu bāzēts lietotāja modelis un piedāvātas trīs jaunas adaptācijā izmantojamās metodes: apmācāmo grupu veidošanas metode, kursa optimālās tēmu secības izveides metode un tēmu secības organizēšanas metode. Izstrādātais lietotāja modelis un adaptācijas metodes nodrošina iespēju katram sistēm…
Intellectual Ability Data Obtaining and Processing for E-Learning System Adaptation
In this article authors describe how an e-learning system can obtain data about learner, so that later it could offer individual content for each learner, based on the obtained data. Authors also describe how the Learning Management System (LMS) Moodle has adapted a standard quiz module interface for testing elementary school students and how students’ individual abilities could be measured more efficiently, for example, by measuring mathematical reaction time. For obtaining necessary testing results and partial processing a new module (TAnalizer) is offered, which is adapted to the Moodle environment. With this module one can gain precise data about each student’s testing process and stude…
The Application of Optimal Topic Sequence in Adaptive e-Learning Systems
In an adaptive e-learning system an opportunity to choose a course topic sequence is given to ensure personalization. The topic sequence can be obtained from three sources: teacher-offered topic sequence that is based on teacher’s pedagogical experience; learner’s free choice that is based on indicated links between topics, and, finally, the optimal topic sequence acquisition method described in this article. The optimal topic sequence is based on previous learners’ experience. With the help of the optimal topic sequence method, data about previous learners’ course topic sequence and course results are obtained. After the data analysis the optimal topic sequence for the specific course is o…
The Use of the Recommended Learning Path in the Personalized Adaptive E-Learning System
This paper promotes the idea of the learning process management in the e-learning system. A personalized adaptive e-learning system is used in this research that comprises three developed topic acquisition sequences: teacher, learner or optimal topic sequences. The learner has the ability to switch between the aforementioned topic sequences. The system stores data about the course acquisition process. The analysis of the stored data demonstrated that a bit more than half of the students used the teacher topic sequence; higher grades in topics got those students who chose the learner or optimal topic sequence; the grades of the half of the students who used the optimal and teacher topic sequ…