Martin Drlík

Impact of Different Pre-Processing Tasks on Effective Identification of Users’ Behavioral Patterns in Web-based Educational System

Abstract Analyzing the unique types of data that come from educational systems can help find the most effective structure of the elearning courses, optimize the learning content, recommend the most suitable learning path based on students behavior, or provide more personalized environment. We focus only on the processes involved in the data preparation stage of web usage mining. Our objective is to specify the inevitable steps that are required for obtaining valid data from the stored logs of the webbased educational system. We compare three datasets of different quality obtained from logs of the web-based educational system and pre-processed in different ways: data with identified users’ sessions and data with the reconstructed path among course activities. We try to assess the impact of these advanced techniques of data pre-processing on the quantity and quality of the extracted rules that represent the learners’ behavioral patterns in a web-based educational system. The results confirm some initial assumptions, but they also show that the path reconstruction among visited activities in e-leaning course has not statistically significant effect on quality and quantity of the extracted rules.

Influence of Different Session Timeouts Thresholds on Results of Sequence Rule Analysis in Educational Data Mining

The purpose of using web usage mining methods in the area of learning management systems is to reveal the knowledge hidden in the log files of their web and database servers. By applying data mining methods to these data, interesting patterns concerning the users’ behaviour can be identified. They help us to find the most effective structure of the e-learning courses, optimize the learning content, recommend the most suitable learning path based on student’s behaviour, or provide more personalized environment. We prepare six datasets of different quality obtained from logs of the learning management system and pre-processed in different ways. We use three datasets with identified users’ sessions based on 15, 30 and 60 minute session timeout threshold and three another datasets with the same thresholds including reconstructed paths among course activities. We try to assess the impact of different session timeout thresholds with or without paths completion on the quantity and quality of the sequence rule analysis that contribute to the representation of the learners’ behavioural patterns in learning management system. The results show that the session timeout threshold has significant impact on quality and quantity of extracted sequence rules. On the contrary, it is shown that the completion of paths has neither significant impact on quantity nor quality of extracted rules.

Probability modelling of accesses to the course activities in the web-based educational system

The aim of the paper is the probability modelling of accesses to the categories of activities of e-learning course in learning management system. We are concerned with the access probabilities to individual activities of e-learning course content depending on the part of the week (workweek and weekend). The probabilities are estimated through multinomial logit model. We pay attention to data preparation issues. We describe used model in more detail and deal with parameter estimations. Finally, we figure that the multinomial logit model finds its application mainly in the process of restructuring the existing e-learning courses. We discuss about its possible contribution to the improvement of the learning management as well as in the personalization of the course content and structure.

E-learning courses quality evaluation framework as part of quality assurance in higher education

The paper introduces the proof of concept of the e-learning courses quality evaluation framework and its implementation into the quality assurance in higher education. We summarize general issues of the internal quality assurance. We pay more attention to the evaluation of the e-learning course quality framework itself in the context of Part 1 of European Standards and Guidelines for internal quality assurance within educational institution. Finally, we try to generalize found observations and create set of procedural rules.

Usage analysis of system for theses acquisition and plagiarism detection

Abstract The national project of The Central Register of the Theses has started in 2008. The project serves as an integrating system for acquisition, archiving and plagiarism detection of the theses from academic information systems of Slovak universities. The first phase of its development has been devoted to the tasks accompanying the processes of acquisition and archiving electronic versions of theses. The national character of the project requires unification of processes associated with theses writing, plagiarism detection and acquisition final versions of the theses from different universities in Slovak republic. The universities, like primary users of this system, have had to adapt their own processes associated with writing, acquisition and archiving of electronic versions of the theses. These inevitable changes have naturally raised many students’ and academic staff’s questions at universities. The same situation has happened at the Constantine the Philosopher University in Nitra and has led to the development of the helpdesk designed for all stakeholders. The helpdesk has provided relevant and digestedly prepared tutorials and discussion forum about abovementioned changes. The activities of the users have been monitored for the purpose of their further processing and identification of the weaknesses of the theses writing, plagiarism detection and acquisition at the university level. The usage analysis of the presented helpdesk and the segmentation method of its users are discussed in detail in the paper. The segmentation method is based on the monitoring of the users’ activities in discussion forums, their searching techniques in available information sources and in posting questions about theses finalization, acquisition and archiving. The authors analyse some aspects of their behavior and discuss interesting findings of the usage analysis of the helpdesk. They give several recommendations for changes in the stakeholder awareness and in the structure of published information materials.

Analysis of Differences between Expected and Observed Probability of Accesses to Web Pages

The paper introduces an alternative method for website analysis that combines two web mining research fields - discovering of web users’ behaviour patterns as well as discovering knowledge from the website structure. The main objective of the paper is to identify the web pages, in which the value of importance of these web pages, estimated by the website developers, does not correspond to the actual perception of these web pages by the visitors. The paper presents a case study, which used the proposed method of the identification suspicious web pages using the analysis of expected and observed probabilities of accesses to the web pages. The expected probabilities were calculated using the PageRank method and observed probabilities were obtained from the web server log file. The observed and expected data were compared using the residual analysis. The obtained results can be successfully used for the identification of potential problems with the structure of the observed website.

Pillar 3 and Modelling of Stakeholders’ Behaviour at the Commercial Bank Website during the Recent Financial Crisis☆

Abstract The paper analyses domestic and foreign market participants’ interests in mandatory Basel 2, Pillar 3 information disclosure of a commercial bank during the recent financial crisis. The authors try to ascertain whether the purposes of Basel 2 regulations under the Pillar 3 - Market discipline, publishing the financial and risk related information, have been fulfilled. Therefore, the paper focuses on modelling of visitors’ behaviour at the commercial bank website where information according to Basel 2 is available. The authors present a detailed analysis of the user log data stored by web servers. The analysis can help better understand the rate of use of the mandatory and optional Pillar 3 information disclosure web pages at the commercial bank website in the recent financial crisis in Slovakia. The authors used association rule analysis to identify the association among content categories of the website. The results show that there is in general a small interest of stakeholders in mandating the commercial banks disclosure of financial information. Foreign website visitors were more concerned about information disclosure according to Pillar 3, Basel 2 regulation, and they have less interest in general information about the bank than domestic ones.

Quantitative and Qualitative Evaluation of Sequence Patterns Found by Application of Different Educational Data Preprocessing Techniques

Educational data preprocessing from log files represents a time-consuming phase of the knowledge discovery process. It consists of data cleaning, user identification, session identification, and path completion phase. This paper attempts to identify phases, which are necessary in the case of preprocessing of educational data for further application of learning analytics methods. Since the sequential patterns analysis is considered suitable for estimating of discovered knowledge, this paper tries answering the question, which of these preprocessing phases has a significant impact on discovered knowledge in general, as well as in the meaning of quality and quantity of found sequence patterns. Therefore, several data preprocessing techniques for session identification and path completion were applied to prepare log files with different levels of data preprocessing. The results showed that the session identification technique using the reference length, calculated from the sitemap, had a significant impact on the quality of extracted sequence rules. The path completion technique had a significant impact only on the quantity of extracted sequence rules. The found results together with the results of the previous systematic research in educational data preprocessing can improve the automation of the educational data preprocessing phase as well as it can contribute to the development of learning analytics tools suitable for different groups of stakeholders engaged in the educational data mining research activities.

Identification of Underestimated and Overestimated Web Pages Using PageRank and Web Usage Mining Methods

The paper describes an alternative method of website analysis and optimization that combines methods of web usage and web structure mining - discovering of web users’ behaviour patterns as well as discovering knowledge from the website structure. Its primary objective is identifying of web pages, in which the value of their importance, estimated by the website developers, does not correspond to the real behaviour of the website visitors. It was proved before that the expected visit rate correlate with the observed visit rate of the web pages. Consequently, the expected probabilities of visiting of web pages by a visitor were calculated using the PageRank method and observed probabilities were obtained from the web server log files using the web usage mining method. The observed and expected probabilities were compared using the residual analysis. While the sequence rules analysis can only uncover the potential problem of web pages with higher visit rate, the proposed method of residual analysis can also consider other web pages with a smaller visit rate. The obtained results can be successfully used for a website optimization and restructuring, improving website navigation, and adaptive website realisation.

Computer science learning activities based on experience

Learning by different ways as well as learning by discovery is natural. Especially in early childhood, we learn mostly by experience. Educational activities designed to acquire knowledge from experience lead students (pupils) to make own abstract or mental models only after finishing the activity. According to our experience, we should conclude that learners really learn from their attempts and mistakes even at computer science classes. Their disengagement should be reduced by the involvement of something personally significant. Teachers should ensure that activities are designed and carried out in ways that offer each learner the chance to engage in the manner that suits them to the best. The paper describes selected computer science activities that should be used to engage the pupils or students in the learning process. We conclude that relatively simple teaching aid could help to explain even abstract computer science underlying concepts through the experience sometimes more effectively than through instructional model.