Accommodating the difference in students’ prior knowledge of cell growth kinetics

This paper describes the development and benefits of an adaptive digital module on cell growth to tackle the problem of educating a heterogeneous group of students at the beginning of an undergraduate course on process engineering. Aim of the digital module is to provide students with the minimal level of knowledge on cell growth kinetics they need to comprehend the content knowledge of the subsequent lectures and pass the exam. The module was organised to offer the subject matter in a differentiated manner, so that students could follow different learning paths. Two student groups were investigated, one consisting of students who had received their prior education abroad and one of students that had not. Exam scores, questionnaires, and logged user data of the two student groups were analysed to discover whether the digital module had the intended effect. The results indicate that students did indeed follow different learning paths. Also, the differences in exam scores between the two student groups that was present before the introduction of the digital module was found to have decreased afterwards. In general, students appreciated the use of the material regardless of their prior education. We therefore conclude that the use of adaptive digital learning material is a possible way to solve the problem of differences in prior education of students entering a course

Student model initialization using domain knowledge ontology representative subset

In intelligent e-learning systems that adapt a learning and teaching process to student knowledge, it is important to adapt the system as quickly as possible. However, adaptation is not possible until the student model is initialized. In this paper, a new approach to student model initialization using domain knowledge representative subset is described. The approach defines which concepts from domain knowledge should be included in the initial test so the system can make conclusions about what students truly know about domain knowledge. This representative subset of domain knowledge is defined using non-semantic mathematical approach based on graph theory. The initial test, created over a domain knowledge representative subset, guarantees encompassing all concepts that are relevant to domain knowledge. A two-level case study is conducted on what would be the representative subset of one selected domain knowledge. It compares semantically selected domain knowledge representative subsets (semantical analysis was done by domain area experts) to a non-semantical, mathematically selected domain knowledge representative subset. The results of the case study show that problems of inequality of semantically selected domain knowledge representative subsets are easily overcome using the presented approachPeer Reviewe

A Methodology for Discovering how to Adaptively Personalize to Users using Experimental Comparisons

We explain and provide examples of a formalism that supports the methodology of discovering how to adapt and personalize technology by combining randomized experiments with variables associated with user models. We characterize a formal relationship between the use of technology to conduct A/B experiments and use of technology for adaptive personalization. The MOOClet Formalism [11] captures the equivalence between experimentation and personalization in its conceptualization of modular components of a technology. This motivates a unified software design pattern that enables technology components that can be compared in an experiment to also be adapted based on contextual data, or personalized based on user characteristics. With the aid of a concrete use case, we illustrate the potential of the MOOClet formalism for a methodology that uses randomized experiments of alternative micro-designs to discover how to adapt technology based on user characteristics, and then dynamically implements these personalized improvements in real time

Sequencing in Intelligent Tutoring Systems based on online learning Recommenders

In dieser Arbeit entwickeln und testen wir Algorithmen für Learning Analytics, die die personalisierte Sequenzierung von Matheaufgaben erlauben. Die Sequenzierung schlägt die nächste Aufgabe einem Schüler vor, die seine Lernbedürfnisse entspricht. Unsere Lösung basiert auf Vygotskys „Zone of Proximal Development“ (ZPD), das die weder zu einfachen noch zu schwierigen Aufgaben für den Schüler bestimmt. Der Sequenzer, auch Vygotsky Policy Sequencer genannt, ist in der Lage Aufgaben im ZPD zu erkennen, dank die von einem Vorhersagealgorithmus geschätzte zukünftige Leistung des Schülers. Die Arbeit enthält folgende Beiträge: (1) Die Evaluation der Anwendbarkeit von Matrix Factorization als Inhaltsdomäne unabhängige Algorithmus für die Vorhersage der Leistung der Schüler. (2) Anpassung und Evaluation eines Matrix Factorization basierenden Algorithmus, der die zeitliche Evolution der Schülerkenntnisse einbezieht. (3) Entwicklung von zwei Ansätzen für die Aktualisierung von Matrix Factorization basierenden Modellen durch den Kalman Filter. Zwei Aktualisierungsfunktionen sind benutzt: (a) eine einfache, die nur die letzte vom Schüler gesehene Aufgabe betrachtet, und (b) eine, die in der Lage ist, seine fehlenden Kompetenzen einzuschätzen. (4) Ein neues Verfahren von Machine Learning gesteuerte Sequenzer zu testen durch die Modellierung einer simulierten Umgebung, die aus simulierte Schülern und Aufgaben mit stetigen erzielten und gebrauchten Fähigkeiten und Schwierigkeitsgraden besteht. (5) Die Entwicklung einer minimal eingreifenden API für die leichte Integration von Machine Learning basierende Komponente in größere Systeme, um das Integrationsrisiko und die Kosten vom Know-How-Transfer zu minimieren. Dank all diesen Beiträgen, wurde der VPS in ein großes kommerzielles System integriert und mit 100 Kinder für einen Monat getestet. Der VPS zeigte Lerneffekte und wahrgenommene Erlebnisse, die mit den von den ITS Sequenzer vergleichbar sind. Infolge der besseren VPS Modellierfähigkeiten konnten die Schüler beendeten die Aufgaben schneller lösen.In this thesis we design and test Learning Analytics algorithms for personalized tasks' sequencing that suggests the next task to a student according to his/her specific needs. Our solution is based on a sequencing policy derived from the Vygotsky's Zone of Proximal Development (ZPD), which denes those tasks that are neither too easy not too dicult for the student. The sequencer, called Vygotsky Policy Sequencer (VPS), can identify tasks in the ZPD thanks to the information it receives from performance prediction algorithms able to estimate the knowledge of the student. Under this context we describe hereafter the thesis contributions. (1) A feasibility evaluation of domain independent Matrix Factorization applied in ITS for Performance Prediction. (2) An adaption and the related evaluation of a domain independent update for online learning Matrix Factorization in ITS. (3) A novel Matrix Factorization update method based on Kalman Filters approach. Two different updating functions are used: (a) a simple one considering the task just seen, and (b) one able to derive the skills' deficiency of the student. (4) A new method for offline testing of machine learning controlled sequencers by modeling simulated environment composed by a simulated students and tasks with continuous knowledge and score representation and different diffculty levels. (5) The design of a minimal invasive API for the lightweight integration of machine learning components in larger systems to minimize the risk of integration and the cost of expertise transfer. Profiting from all these contributions, the VPS was integrated in a commercial system and evaluated with 100 children over a month. The VPS showed comparable learning gains and perceived experience results with those of the ITS sequencer. Finally, thanks to its better modeling abilities, the students finish faster the assigned tasks

Third international workshop on Authoring of adaptive and adaptable educational hypermedia (A3EH), Amsterdam, 18-22 July, 2005

The A3EH follows a successful series of workshops on Adaptive and Adaptable Educational Hypermedia. This workshop focuses on models, design and authoring of AEH, on assessment of AEH, conversion between AEH and evaluation of AEH. The workshop has paper presentations, poster session and panel discussions

Expert-Generated and Auto-Generated Socratic Tutoring Systems For Code Comprehension

Programming skills are a vital part of many disciplines but can be challenging to teach and learn. Thus, the programming courses are considered difficult and a major stumbling block. To overcome these challenges, students could benefit from extensive individual support such as tutoring, but there are simply not enough qualified tutors available to meet rising demands.A potential solution is the development of intelligent tutoring systems (ITSs), which offer individualized, one-on-one instruction. Such systems can offer the support to make programming instruction more effective, scalable and reduce existing teachers\u27 workloads.This dissertation demonstrates how conversational ITSs and the Socratic method of teaching can improve a novice\u27s understanding of programming concepts and, in particular, the scaffolding of code comprehension processes. Furthermore, this work provides a novel method to automatically author a Socratic dialogue-based ITS. Indeed, two major outcomes of this work are a Socratic dialogue-based ITS and an automated dialogue authoring tool, which generates full Socratic dialogue from Java source code.The key objectives of this dissertation were, first, to determine whether the Socratic method would be effective at eliciting learners to engage in self-explanations with the help of the Socratic Tutor ITS and, second, to assess the quality of Socratic Author\u27s auto-generated tutorial dialogue. Thus, the work presented here sought to answer two main research questions: (1) can a Socratic ITS lead to improved code comprehension? and (2) to what extent can Socratic dialogue be generated automatically?In sum, this research helps establish a relationship between code comprehension and the use of the Socratic method in learning computer programming. Furthermore, the work introduces a novel approach for generating Socratic dialogue from source code with examples for the Java programming language. The auto-authoring tool could help teachers and ITS developers create tutorial dialogues automatically from Java code without requiring nondomain knowledge. To the best of our knowledge, no such auto-generation of tutorial dialogues from source code has been done before and thus constituting a premiere

Designing web-based adaptive learning environment : distils as an example

In this study, two components are developed for the Web-based adaptive learning: an online Intelligent Tutoring Tool (ITT) and an Adaptive Lecture Guidance (ALG). The ITT provides students timely problem-solving help in a dynamic Web environment. The ALG prevents students from being disoriented when a new domain is presented using Web technology. A prototype, Distributed Intelligent Learning System (DISTILS), has been implemented in a general chemistry laboratory domain. In DISTILS, students interact with the ITT through a Web browser. When a student selects a problem, the problem is formatted and displayed in the user interface for the student to solve. On the other side, the ITT begins to solve the problem simultaneously. The student can then request help from the ITT through the interface. The ITT interacts with the student, verifying those solution activities in an ascending order of the student knowledge status. In DISTILS, a Web page is associated with a HTML Learning Model (HLM) to describe its knowledge content. The ALG extracts the HLM, collects the status of students\u27 knowledge in HLM, and presents a knowledge map illustrating where the student is, how much proficiency he/she already has and where he/she is encouraged to explore. In this way, the ALG helps students to navigate the Web-based course material, protecting them from being disoriented and giving them guidance in need. Both the ITT and ALG components are developed under a generic Common Object Request Broker Architecture (CORBA)-driven framework. Under this framework, knowledge objects model domain expertise, a student modeler assesses student\u27s knowledge progress, an instruction engine includes two tutoring components, such as the ITT and the ALG, and the CORBA-compatible middleware serves as the communication infrastructure. The advantage of such a framework is that it promotes the development of modular and reusable intelligent educational objects. In DISTILS, a collection of knowledge objects were developed under CORBA to model general chemistry laboratory domain expertise. It was shown that these objects can be easily assembled in a plug-and-play manner to produce several exercises for different laboratory experiments. Given the platform independence of CORBA, tutoring objects developed under such a framework have the potential to be easily reused in different applications. Preliminary results showed that DISTILS effectively enhanced learning in Web environment. Three high school students and twenty-two NJIT students participated in the evaluation of DISTILS. In the final quiz of seven questions, the average correct answers of the students who studied in a Web environment with DISTILS (DISTILS Group) was 5.3, and the average correct answers of those who studied in the same Web environment without DISTILS (NoDISTILS Group) was 2.75. A t-test conducted on this small sample showed that the DISTILS group students significantly scored better than the NoDISTILS group students

Connecting electronic portfolios and learner models

Using electronic portfolios (e-portfolios) to assist learning is an important component of future educational models. A portfolio is a purposeful collection of student work that exhibits the student's efforts, progress and achievements in one or more areas. An e-portfolio contains a variety of information about a person's learning outcomes, such as artifacts, assertions from others, self-reflective information and presentation for different purposes. E-portfolios become sources of evidence for claims about prior conceptual knowledge or skills. This thesis investigates using the information contained in e-portfolios to initialize the learner model for an intelligent tutoring system. We examine the information model from the e-portfolio standardized specification and present a method that may assist users in initializing learner models using e-portfolios as evidence for claims about prior conceptual knowledge or skills. We developed the EP-LM system for testing how accurately a learner model can be built and how beneficial this approach can be for reflective and personalized learning. Experimental results are presented aiming at testing whether accurate learner models can be created through this approach and whether learners can gain benefits in reflective and personalized learning. Monitoring this process can also help ITS developers and experts identify how an initial learner model can automatically arise from an e-portfolio. Additionally, a well-structured learner model, generated by an intelligent tutoring system also can be attached to an e-portfolio for further use by the owner and others

Conception of an E-learning scheme at the University of Algarve

With the proliferation of the Internet use, a growth of e-learning courses has been verified. We arrived to the moment where it is not enough for Universities to have standard courses to offer to the students, because there is an increasing population which tends to choose his formation according to their objectives, styles, needs and learning preferences (the student profile). This way, the universities are faced with a new challenge, which is to offer, together with the standard courses, modules specially tailored to the user desires, based on the identification of the customers needs. In this paper, a model for the distance formation through Internet is discussed, that is being developed in the University of Algarve, which makes possible each individual to learn in agreement with his/her profile