An open learner model for trainee pilots

This paper investigates the potential for simple open learner models for highly motivated, independent learners, using the example of trainee pilots. In particular we consider whether such users access their learner model to help them identify their current knowledge level, areas of difficulty and specific misconceptions, to help them plan their immediate learning activities; and whether they find a longer‐term planning aid useful. The Flight Club open learner model was deployed in a UK flight school over four weeks. Results suggest that motivated users such as trainee pilots will use a system with a simple open learner model, and are interested in consulting their learner model information both to facilitate planning over time, and to understand their current knowledge state. We discuss the extent to which our findings may be relevant to learners in other contexts

Investigating the Impact of Learners’ Learning Styles on the Acceptance of Open Learner Models for Information Sharing

Individual differences in learners’ learning styles can have a significant effect on their acceptance of collaboration technologies to facilitate the sharing of learning information in technology-based collaborative learning. There is, however, a lack of understanding of the impact of learning styles on the acceptance of open learner models as a collaboration technology for information sharing. This study investigates the impact of learners’ learning styles on their acceptance of open learner models for information sharing. A total of 240 undergraduate students in a university in Malaysia have participated in the online survey. A chi-square test is performed to explore the relationship between learning styles and the acceptance of open learner models for information sharing in technology-based collaborative learning. The result reveals that learning styles have no significant impact on learners’ acceptance of open learner models for information sharing. The implications of this study can assist open learner models designers to apply appropriate instructional design strategies in developing open learner models applications

Supporting mediated peer-evaluation to grade answers to open-ended questions

We show an approach to semi-automatic grading of answers given by students to open ended questions (open answers). We use both peer-evaluation and teacher evaluation. A learner is modeled by her Knowledge and her assessments quality (Judgment). The data generated by the peer- and teacher- evaluations, and by the learner models is represented by a Bayesian Network, in which the grades of the answers, and the elements of the learner models, are variables, with values in a probability distribution. The initial state of the network is determined by the peer-assessment data. Then, each teacher’s grading of an answer triggers evidence propagation in the network. The framework is implemented in a web-based system. We present also an experimental activity, set to verify the effectiveness of the approach, in terms of correctness of system grading, amount of required teacher's work, and correlation of system outputs with teacher’s grades and student’s final exam grade

A Multi-Dimensional Measurement Model for Assessing the Pre-Adoption of Open Learner Models in Technology-Mediated Teaching and Learning: A Pilot Study

Visualizing learners’ information through the development of open learner models for improving the effectiveness of teaching and learning has attracted much attention in technology-mediated learning. There is, however, a lack of research in exploring the acceptance of open learner models in the pre-adoption of this model. This paper develops a multi-dimensional measurement model for assessing the pre-adoption of open learner models from the learners’ perspective. A pilot study is carried out to confirm the reliability and validity of the measurement model based on the data collected from 300 respondents using an online survey distributed in a higher education institution in Malaysia. This model provides a useful set of guidelines for educational institutions in developing efficient and effective policies to promote the adoption of open learner models in technology-mediated learning towards improving the performance of technology-mediated teaching and learning

Belief Exploration in a Multiple-Media Open Learner Model for Basic Harmony

Abstract. This paper focuses on whether learners of basic music theory may find a multiple-media independent open learner model useful to explore their knowledge of harmony concepts. Learners were given the option to explore example beliefs held in their learner model as music notation, audio or text, and shown how their beliefs compared to those of an expert. Results suggest users are both willing and make use of the open learner model, and show individual preferences for media format in which to view their beliefs. Participants mostly explored incorrect knowledge even though more correct knowledge was present in the model, and made greater use of the views specific to the music domain (music notation, audio) when their model showed “incorrect knowledge”. Results indicate the potential to include multi-media information in open learner models in appropriate domains

Learners Thrive When Using Multifaceted Open Social Learner Models

This article explores open social learner modeling (OSLM)-a social extension of open learner modeling (OLM). A specific implementation of this approach is presented by which learners' self-direction and self-determination in a social e-learning context could be potentially promoted. Unlike previous work, the proposed approach, multifaceted OSLM, lets the system seamlessly and adaptively embed visualization of both a learner's own model and other learning peers' models into different parts of the learning content, for multiple axes of context, at any time during the learning process. It also demonstrates the advantages of visualizing both learners' performance and their contribution to a learning community. An experimental study shows that, contrary to previous research, the richness and complexity of this new approach positively affected the learning experience in terms of perceived effectiveness, efficiency, and satisfaction. This article is part of special issue on social media for learning

Active support for instructors and students in an online learning environment

By opening the learner model to both the learner and other peers within an e-learning system, the learner gains control over his or her learner model and is able to reflect on the contents presented in the model. Many current modeling systems translate an existing model to fit the context when information is needed. This thesis explores the observation that information in the model depends on the context in which it is generated and describes a method of generating the model for the specific user and purpose. The main advantage of this approach is that exactly the right information is generated to suit the context and needs of the learner. To explore the benefits and possible downsides of this approach, a learner model Query Tool was implemented to give instructors and learners the opportunity to ask specific questions (queries) of the content delivery system hosting several online courses. Information is computed in real time when the query is run by the instructor, so the data is always up-to-date. Instructors may then choose to allow students to run the query as well, enabling learner reflection on their progress in the course as the instructor has defined it. I have called this process active open learner modelling, referring to the open learner modelling community where learner models are accessible by learners for reflective purposes, and referring to the active learner modelling community which describes learner modelling as a context-driven process. Specific research questions explored in this thesis include "how does context affect the modelling process when learner models are opened to users", "how can privacy be maintained while useful information is provided", and "can an accurate and useful learner model be computed actively"

Individual and peer comparison open learner model visualisations to identify what to work on next

Open learner models (OLM) can support self-regulated learning, collaborative interaction, and navigation in adaptive educational systems. Previous research has found that learners have a range of preferences for learner model visualisation. However, research has focused mainly on visualisations that are available in a single system, meaning that not all visualisations have been compared to each other. We present a study using screen shots of OLM visualisations for individuals and for comparing one's own learner model to the models of other individuals or the group, to define visualisations that students would be able to use to identify their next steps, across a wider range of options

Creating Shareable Knowledge: Exploring the Synergy between Metaliteracy and Open Pedagogy

Open educational resources (OERs) have created conditions for a transformational change in teaching and learning. New models and frameworks provide the basis for innovative, learner-centered pedagogical practices. Open pedagogy, which builds upon the use of OERs and open educational practices, envisages learners as knowledge creators. Metaliteracy proposes a number of active, reflective learner roles, with a particular emphasis on online, participatory environments. Learners who find themselves in open pedagogical situations may feel anxiety and uncertainty concerning the unaccustomed environment and expectations placed upon them. Metaliteracy provides a comprehensive scaffolding and flexible framework for the learning required in such settings, a development that extends life-long and life-wide. This presentation will explore the synergistic relationship between metaliteracy and open pedagogy that enhances learner engagement and empowerment. Several examples will be explored, including a course in which students edited and created Wikipedia articles within a metaliteracy framework

A Toolbox for Modelling Engagement with Educational Videos

With the advancement and utility of Artificial Intelligence (AI), personalising education to a global population could be a cornerstone of new educational systems in the future. This work presents the PEEKC dataset and the TrueLearn Python library, which contains a dataset and a series of online learner state models that are essential to facilitate research on learner engagement modelling.TrueLearn family of models was designed following the "open learner" concept, using humanly-intuitive user representations. This family of scalable, online models also help end-users visualise the learner models, which may in the future facilitate user interaction with their models/recommenders. The extensive documentation and coding examples make the library highly accessible to both machine learning developers and educational data mining and learning analytics practitioners. The experiments show the utility of both the dataset and the library with predictive performance significantly exceeding comparative baseline models. The dataset contains a large amount of AI-related educational videos, which are of interest for building and validating AI-specific educational recommenders.Comment: In Proceedings of AAAI Conference on Artificial Intelligence 2024. arXiv admin note: text overlap with arXiv:2309.1152