Modeling students’ behavioral engagement through different in-class behavior styles

Background The growing necessity of providing better education, notably through the development of Adaptive Learning Systems (ALSs), leveraged the study of several psychological constructs to accurately characterize learners. A concept extensively studied in education is engagement, a multidimensional construct encompassing behavioral expression and motivational backgrounds. This metric can be used to not only guide certain pedagogic methodologies, but also to endow systems with the right tutoring techniques. As such, this article aims to inspire improved teaching styles and automatic learning systems, by experimentally verifying the influence of in-class behaviors in students’ engagement. Results Over 16 math lessons, the occurrence of students’ and instructors’ behaviors, alongside students’ engagement estimates, were recorded using the COPUS observation protocol. After behavior-profiling the classes deploying such lessons, significant linear models were computed to relate the frequency of the students’ or instructors’ behaviors with the students’ engagement at different in-class periods. The models revealed a positive relation of students’ initial individual thinking and later group activity participation with their collective engagement, as well as a positive engagement relation with the later application of instructor’s strategies such as giving feedback and moving through class, guiding on-going work. Conclusions The results suggest the benefit of applying a workshop-like learning process, providing more individual explanations and feedback at the beginning of an interaction, leaving collective feedback and students’ guidance of on-going work for later on. Based on the relations suggested by our models, several guidelines for developing ALSs are proposed, and a practical illustrative example is formulated.info:eu-repo/semantics/publishedVersio

Inclusive Intelligent Learning Management System Framework - Application of Data Science in Inclusive Education

Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data ScienceBeing a disabled student the author faced higher education with a handicap which as experience studying during COVID 19 confinement periods matched the findings in recent research about the importance of digital accessibility through more e-learning intensive academic experiences. Narrative and systematic literature reviews enabled providing context in World Health Organization’s International Classification of Functioning, Disability and Health, legal and standards framework and information technology and communication state-of-the art. Assessing Portuguese higher education institutions’ web sites alerted to the fact that only outlying institutions implemented near perfect, accessibility-wise, websites. Therefore a gap was identified in how accessible the Portuguese higher education websites are, the needs of all students, including those with disabilities, and even the accessibility minimum legal requirements for digital products and the services provided by public or publicly funded organizations. Having identified a problem in society and exploring the scientific base of knowledge for context and state of the art was a first stage in the Design Science Research methodology, to which followed development and validation cycles of an Inclusive Intelligent Learning Management System Framework. The framework blends various Data Science study fields contributions with accessibility guidelines compliant interface design and content upload accessibility compliance assessment. Validation was provided by a focus group whose inputs were considered for the version presented in this dissertation. Not being the purpose of the research to deliver a complete implementation of the framework and lacking consistent data to put all the modules interacting with each other, the most relevant modules were tested with open data as proof of concept. The rigor cycle of DSR started with the inclusion of the previous thesis on Atlântica University Institute Scientific Repository and is to be completed with the publication of this thesis and the already started PhD’s findings in relevant journals and conferences

Personality representation: predicting behaviour for personalised learning support

The need for personalised support systems comes from the growing number of students that are being supported within institutions with shrinking resources. Over the last decade the use of computers and the Internet within education has become more predominant. This opens up a range of possibilities in regard to spreading that resource further and more effectively. Previous attempts to create automated systems such as intelligent tutoring systems and learning companions have been criticised for being pedagogically ineffective and relying on large knowledge sources which restrict their domain of application. More recent work on adaptive hypermedia has resolved some of these issues but has been criticised for the lack of support scope, focusing on learning paths and alternative content presentation. The student model used within these systems is also of limited scope and often based on learning history or learning styles.This research examines the potential of using a personality theory as the basis for a personalisation mechanism within an educational support system. The automated support system is designed to utilise a personality based profile to predict student behaviour. This prediction is then used to select the most appropriate feedback from a selection of reflective hints for students performing lab based programming activities. The rationale for the use of personality is simply that this is the concept psychologists use for identifying individual differences and similarities which are expressed in everyday behaviour. Therefore the research has investigated how these characteristics can be modelled in order to provide a fundamental understanding of the student user and thus be able to provide tailored support. As personality is used to describe individuals across many situations and behaviours, the use of such at the core of a personalisation mechanism may overcome the issues of scope experienced by previous methods.This research poses the following question: can a representation of personality be used to predict behaviour within a software system, in such a way, as to be able to personalise support?Putting forward the central claim that it is feasible to capture and represent personality within a software system for the purpose of personalising services.The research uses a mixed methods approach including a number and combination of quantitative and qualitative methods for both investigation and determining the feasibility of this approach.The main contribution of the thesis has been the development of a set of profiling models from psychological theories, which account for both individual differences and group similarities, as a means of personalising services. These are then applied to the development of a prototype system which utilises a personality based profile. The evidence from the evaluation of the developed prototype system has demonstrated an ability to predict student behaviour with limited success and personalise support.The limitations of the evaluation study and implementation difficulties suggest that the approach taken in this research is not feasible. Further research and exploration is required –particularly in the application to a subject area outside that of programming

Ad hoc transient communities::towards fostering knowledge sharing in learning networks

Berlanga, A. J., Sloep, P. B., Kester, L., Brouns, F., Van Rosmalen, P., & Koper, R. (2008). Ad hoc transient communities: towards fostering knowledge sharing in Learning Networks. International Journal of Learning Technology, 3(4), 443-458.Sociability is conducive to learning effectiveness and efficiency. Sociability does not emerge easily in Learning Networks. This paper argues that so-called ad hoc transient communities will help the emergence of sociability in Learning Networks. Ad hoc transient communities are relatively small, temporal and goal-directed communities that support voluntary, emergent, informal knowledge sharing. The paper examines various theories, management policies and technological prerequisites that underpin their proper functioning. Venues for future research, both conceptual and empirical are discussed.The work on this publication has been sponsored by the TENCompetence Integrated Project that is funded by the European Commission's 6th Framework Programme, priority IST/Technology Enhanced Learning. Contract 027087 [http://www.tencompetence.org

An Investigation Of The Relationship Between The Use Of Modern Digital Technologies, Language Learning Strategies, And Development Of Second Language Skills

Like many other areas of human knowledge, the field of language learning has undergone changes as a consequence of the application of digital technologies. Extensive exposure and anytime and anywhere access availability to data in a second or foreign language (L2) bring almost unlimited learning opportunities for digital age students, which affects their learning behaviors also known as language learning strategies (LLS). The purpose of the present study is to define preferred LLS patterns of digitally native L2 learners and to establish relationships between types of existing digital technologies, learners’ demographic characteristics, and the use of learning strategies to support the development of specific language skills and aspects. The setting for this study was made up by a medium-sized university in the northern U.S., particularly, its undergraduate student population enrolled in foreign language courses in the Department of Modern and Classical Languages and Literatures during the 2021 fall semester. They were asked to complete a survey that contained the original validated version of the Strategy Inventory for Language Learning (SILL) instrument (Oxford, 1990) and three additional sections disclosing the participants’ demographics, technology use experience, and targeted language skills and aspects. Both descriptive and inferential quantitative methods of data analysis were used in the study to elucidate the research questions. A number of analytic procedures using SPSS® Statistics software were performed to find out detailed statistic values of the research variables. Frequencies and descriptive statistics, analysis of correlations, extreme groupings t-tests to explore the relationships between the subsets of categorical variables, and factor analysis of LLS domains were implemented to identify meaningful patterns of technology use in L2 learning. Data from this study provide a view of how the Digital Natives themselves see their technology use and approaches to learning. Research conclusions based on obtained self-reported evidence allow us to make broader recommendations for changes in the L2 teaching methodology. They may also prevent instructors from making unsupported assumptions about their students\u27 mastery of educational technology, and, thereby, from neglecting to teach students the skills they need for academic success. Keywords: digital native learner, digital technology categories, language learning strategies, L2 language skill

Evaluation of the development and application of multimedia computer assisted learning in Higher Education.

This thesis deals with approaches to the evaluation of multimedia computer assisted learning in higher education. The thesis is presented in two parts. The first part consists mainly of a literature based review of the rationale and methods employed in the development of multimedia CAL systems focusing on the ability of such systems to deliver a variety of pedagogic aims and objectives which the literature on the subject generally attributes to them. This was done in order to identify and examine the important features which should be incorporated in the effective evaluation of such systems. 1) the pedagogical basis of multimedia learning environments with particular reference to the mechanism by which they claim to encourage an approach to learning which facilitates 'deep' rather than 'shallow' learning' (Chapters 3 and 4); 2) the basis on which multimedia CAL systems claim to provide interactive learning environments which allow the teaching materials to be tailored by learners to accommodate their own individual preferences for adopting particular learning strategies. In particular this focused on the importance of individual learning styles and learners' degree of computer confidence (Chapter 5); 3) the institutional/delivery factors which must be understood to explain fully the context in which evaluations are carried out and which may have important effects on the outcomes of evaluation (Chapter 6). This literature review, together with a practical survey of a range of existing CAL courseware and an e-mail survey of CAL developers provides the basis for presenting an approach to evaluation which differentiates systems on the basis of the pedagogic approach they adopt and the context in which they are implemented. Finally, a critical review of existing evaluation methods was undertaken and important elements within these methods were incorporated into a new framework for evaluation. The framework provides a tool for determining an evaluation strategy that encompasses all stages of development, formative and summative evaluation of CAL courseware. Evaluation is based on the explicit aims and objectives of the courseware being provided and is moderated by contextual factors that define the pedagogical approach being taken, any individual learner differences that must be taken into account, and the institutional/delivery context within which the courseware is used. An analysis of the implications of the framework when formulating an evaluation strategy demonstrates weaknesses in the assessment instruments currently being used in evaluation studies - particularly for providing reliable measures of 'learning effect' as part of summative evaluation and also with respect to accurate quantification of costs associated with development and use of CAL courseware. The second part of the thesis tests the framework. The approach taken was to develop and formatively and summatively assess a multimedia CAL system used to teach parts of a course on bibliographic classification to students at the Robert Gordon University in Aberdeen. Qualitative and quantitative tests to accomplish this are described and the result of statistical analyses of learner performance when using the system are presented. This empirical study provides further insights into the practical problems involved in developing and evaluating a multimedia CAL system and in particular highlights: 1) the influence which individual learning style (as measured by the Gregorc Style Delineator) has on student performance in a context in which postgraduate students were required to use the CAL courseware rather than attend lectures - results indicate that CAL does not serve all learners equally; 2) the importance of the delivery context in a study in which undergraduate students were provided with CAL materials to supplement the delivery of their course. The evaluation framework was found to be a robust framework for developing and testing didactic teaching packages which were developed in the context of improving the quality of the teaching and learning of bibliographic classification to both undergraduate and postgraduate students. Recommendations are provided for future research based on using the framework to explore other contexts in which courseware is developed and implemented

E-Learning and Digital Education in the Twenty-First Century

E-learning and digital education approaches are evolving and changing the landscape of teaching and learning at all levels of education throughout the world. Innovation of emerging learning technologies is assisting e-learning and digital education to meet the needs of the 21st century. Due to the digital transformation of everyday practice, the process of learning and education has become more self-paced and accessible at any time from anywhere. The new generations of digital natives are growing up with a set of skills through their engagement with the digital world. In this context, this book includes a collection of chapters to facilitate continuous improvements including flexibility and accessibility in e-learning and digital education by exploring the challenges and opportunities of innovative approaches through the lenses of current theories, policies, and practices

AI ethics and higher education : good practice and guidance for educators, learners, and institutions

Artificial intelligence (AI) is exerting unprecedented pressure on the global higher educational landscape in transforming recruitment processes, subverting traditional pedagogy, and creating new research and institutional opportunities. These technologies require contextual and global ethical analysis so that they may be developed and deployed in higher education in just and responsible ways. To-date, these efforts have been largely focused on small parts of the educational environments leaving most of the world out of an essential contribution. This volume acts as a corrective to this and contributes to the building of competencies in ethics education and to broader, global debates about how AI will transform various facets of our lives, not the least of which is higher education