User-Centered Evaluation of Adaptive and Adaptable Systems

Adaptive and adaptable systems provide tailored output to various users in various contexts. While adaptive systems base their output on implicit inferences, adaptable systems use explicitly provided information. Since the presentation or output of these systems is adapted, standard user-centered evaluation methods do not produce results that can be easily generalized. This calls for a reflection on the appropriateness of standard evaluation methods for user-centered evaluations of these systems. We have conducted a literature review to create an overview of the methods that have been used. When reviewing the empirical evaluation studies we have, among other things, focused on the variables measured and the implementation of results in the (re)design process. The goal of our review has been to compose a framework for user-centered evaluation. In the next phase of the project, we intend to test some of the most valid and feasible methods with an adaptive or adaptable system

NoTube – making TV a medium for personalized interaction

In this paper, we introduce NoTube’s vision on deploying semantics in interactive TV context in order to contextualize distributed applications and lift them to a new level of service that provides context-dependent and personalized selection of TV content. Additionally, lifting content consumption from a single-user activity to a community-based experience in a connected multi-device environment is central to the project. Main research questions relate to (1) data integration and enrichment - how to achieve unified and simple access to dynamic, growing and distributed multimedia content of diverse formats? (2) user and context modeling - what is an appropriate framework for context modeling, incorporating task-, domain and device-specific viewpoints? (3) context-aware discovery of resources - how could rather fuzzy matchmaking between potentially infinite contexts and available media resources be achieved? (4) collaborative architecture for TV content personalization - how can the combined information about data, context and user be put at disposal of both content providers and end-users in the view of creating extremely personalized services under controlled privacy and security policies? Thus, with the grand challenge in mind - to put the TV viewer back in the driver's seat – we focus on TV content as a medium for personalized interaction between people based on a service architecture that caters for a variety of content metadata, delivery channels and rendering devices

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

Using adaptive hypermedia to support diversity in secondary schools

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. F. Muñoz, and A. Ortigosa, “Using adaptive hypermedia to support diversity in secondary schools”, in Sixth International Conference on Advanced Learning Technologies, 2006, Kerkrade, 2006, pp. 1055-1059Attention to diversity is growing concern in public secondary schools in Spain. This paper presents an assessment about the use of adaptive hypermedia technology for supporting diversity. Three experiences were carried out with an adaptive course on mathematics to test the effects of this technology on the heterogeneous population of secondary schools. Their results and conclusions are also presentedThis work has been funded by the Spanish Ministry of Science and Education, TIN2004-03140

Representing adaptive and adaptable Units of Learning:How to model personalized eLearning in IMS Learning Design

Burgos, D., Tattersall, C., & Koper, E. J. R. (2007). Representing adaptive and adaptable Units of Learning. How to model personalized eLearning in IMS Learning Design. In B. Fernández Manjon, J. M. Sanchez Perez, J. A. Gómez Pulido, M. A. Vega Rodriguez & J. Bravo (Eds.), Computers and Education: E-learning - from theory to practice. Germany: Kluwer.In this chapter we examine how to represent adaptive and adaptable Units of Learning with IMS Learning Design in order to promote automation and interoperability. Based on a literature study, a distinction is drawn between eight types of adaptation that can be classified in three groups: a) the main group, with interfaced-base, learning-flow and content-base; b) interactive problem solving support, adaptive information filtering, adaptive user grouping; and c) adaptive evaluation and changes on-the-fly. Several sources of information are used in adaptation: user, teacher and set of rules. In this paper, we focus on the core group a). Taking the various possible inputs to an eLearning process, we analyze how to model personalized learning scenarios related to these inputs explaining how these can be represented in IMS Learning Design

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

Modelling of pedagogical patterns through e-learning objects

Програмні платформи для електронного навчання підтримують різні варіанти подання навчального контенту. Одним із способів для його організації та структурування є так звані педагогічні моделі. Вони є методом для відображення і розповсюдження отриманих знань та практичного досвіду. Педагогічні моделі використовуються для опису педагогічних ситуацій, які неодноразово виникають під час навчання. У контексті систем електронного навчання існують різні підходи до цифровізації педагогічних моделей. Мета роботи – показати, як побудувати педагогічні моделі, використовуючи педагогічні об’єкти електронного навчання, які можна легко та зручно впровадити як моделі в адаптивному середовищі електронного навчання. Педагогічний об’єкт електронного навчання – це абстрактне поняття, яке може бути представлено в конкретній формі об’єкта електронного навчання, методичного об’єкта електронного навчання, об’єкта електронного навчання для моніторингу та діагностики чи об’єкта електронного навчання з результатами навчання. Ці об'єкти є базовими блоками для побудови педагогічних моделей. У даній роботі детально розглянуто питання створення педагогічних моделей з використанням чотирьох типів педагогічних об’єктів електронного навчання. Представлений приклад педагогічної моделі призначений для досягнення певних освітніх цілей. Приклади моделей, створених з використанням певних об’єктів електронного навчання, представляють навчальні блоки, які використовуються залежно від контексту певної педагогічної ситуації. Педагогічні об’єкти електронного навчання та педагогічні моделі, призначені для їх застосування як засоби навчання в адаптивному середовищі електронного навчання, застосовуються в Moodle LMS відповідно до тенденції програмного забезпечення з метою допомоги викладачу або заміни деяких його функцій, а роль викладача піднімається на більш високий організаційний, педагогічний та методичний рівень. За допомогою педагогічних об’єктів електронного навчання створено три приклади педагогічних моделей: «Ранній зворотний зв’язок», «Сендвіч - метод зворотного зв’язку» та «Послідовна метафора» в LMS Moodle, які були апробовані в навчальному курсі «Моделювання навчальних курсів у Moodle» під час осіннього триместру 2021/2022 навчального року на факультеті математики та інформатики Пловдивського університету “Паїсій Хілендарський”, Болгарія.Software platforms for e-learning support various options for presenting educational content. One of the ways to organize and structure it is via so-called pedagogical patterns. They are a method for describing and sharing knowledge and practical experience. Pedagogical patterns are used to describe pedagogical situations that occur repeatedly in the learning process. In the context of e-learning systems, there are various approaches to digitalization of pedagogical patterns. The purpose of the paper is to show how to build instances of pedagogical patterns using e-learning pedagogical objects, which can be easily and conveniently used as models in an adaptive e-learning environment. An e-learning pedagogical object is an abstract concept that can be presented in the concrete form of an e-learning object, an e-learning methodological object, an e-learning object for monitoring and diagnostics or an e-learning object with learning outcomes. These objects are building blocks for constructing instances of pedagogical patterns. This paper thoroughly discusses the issue of creating instances of pedagogical patterns of the four types of e-learning pedagogical objects. The instance of a pedagogical pattern is meant to serve to create subsections of educational topics. The instances of the patterns built of e-learning objects are learning units that are used depending on the context of a particular pedagogical situation. The e-learning pedagogical objects and the pedagogical pattern instances are intended to be applied in an adaptive e-learning environment as teaching aids. Their theoretical models are applied in Moodle LMS in line with the tendency for software to assist and replace some of the teacher functions, while the teacher’s role is raised to a higher organizational, pedagogical and methodological level. Three instances of pedagogical patterns have been created through e-learning pedagogical objects: “Early Feedback”, “Feedback Sandwich” and “Consistent Metaphor” in LMS Moodle, which have been tested in the training course “Modeling of training courses in Moodle” during the autumn trimester of the academic year 2021/2022 at the Faculty of Mathematics and Informatics of Paisii Hilendarski University of Plovdiv, Bulgaria