Open Student Models Research Articles

Open Student Modeling Research and its Connections to Educational Assessment

Research in the area of Open Student Models (OSMs) has shown that external representations of the student model can be used to facilitate educational processes such as student reflection, knowledge awareness, learning, collaboration, negotiation, and student model diagnosis. OSMs can be integrated into existing learning systems or become a framework for the creation of learning systems. This paper discusses how early work with Jim Greer in the area of open student modeling has inspired and continues to inspire a line of research on innovative assessments and the design and evaluation of score report systems that are used to share assessment/student modeling information with various educational stakeholders to support learning. Several projects are discussed as well as their connections to my work with Jim while working at the ARIES laboratory.

Technology-enhanced assessment visualization for smart learning environments

In Smart Learning Environments, students need to be aware of their academic performance so they can self-regulate their learning process. Likewise, the teaching process can also be improved if instructors are able to supervise the progress of students, both individually and globally, and anticipate proper pedagogical strategies. Thus, effective Student Models, capable of identifying and predicting the level of knowledge of students, are a key requirement in modern educational systems. In this article, we revisit OSM-V, an Open Student Model with Information Visualization capabilities that allow students and instructors to assess performance-related information in educational systems. We detail its architecture and how it was integrated into Classroom eXperience, a Smart Learning Environment with multimedia capture capabilities. We also present extended results from experiments that evaluate both the perception of utility and behavioral changes in students who used OSM-V, showing that it can positively impact students’ learning and positively influence their study habits.

Utilising problem-solving: from self-assessment to self regulating

ABSTRACTWith the wide adoption of online platforms in education, having the content organised and readily available for the learners to self-assess their progress is crucial to ensure academic success. However, without the support of an active mentor, it might be difficult for the learners to guide themselves on how to accurately evaluate their learning outcome. This article focuses on how students benefited from self-assessing their programming course progress using an adaptive platform, namely QuizIT. We discuss the self-assessment procedure and development as it progresses into an open student model learning platform. The initial release was designated to assist programming novices as they encounter the programming learning journey. It was then followed by an extension to open the possibilities to the learner by having access to the learning model and gaining more control over the assessment experience. Quiz Adapt, was the set of features that provided an adaptive recommender based on an open learner model. The data collected from four study setups are evaluated to show the impact on the learning gain from interacting with the system. In addition, this paper sheds light on the effectiveness of daily learning opportunities in the introductory phase of education.

Guiding and Motivating Students through Open Social Student Modeling: Lessons Learned

Background/Context A large number of educational resources are now made available on the web to support both regular classroom learning and online learning. The abundance of available content has produced at least two problems: how to help students find the most appropriate resources and how to engage them in using and benefiting from these resources. Personalized and social learning have been suggested as potential ways to address these problems. Our work attempts to integrate these directions of research by combining the ideas of adaptive navigation support and open student modeling with the ideas of social comparison and social visualization. We call our approach Open Social Student Modeling (OSSM). Objective/Research Questions First, we review a sequence of our earlier projects focused on Open Social Student Modeling for one kind of learning content and formulate several key design principles that contribute to the success of OSSM. Second, we present our exploration of OSSM in a more challenging context of modeling student progress for two kinds of learning content in parallel. We aim to answer the following research questions: How do we design OSSM interfaces to support many kinds of learning content in parallel? Will current identified design principles (key features) confirm the power of the learning community through OSSM with multiple learning-resource collections? Will the OSSM visualization provide successful personalized guidance within a richer collection of educational resources? Research Design We designed four classroom studies to assess the value of different options for OSSM visualization of one and multiple kinds of learning content in the context of programming-language learning. We examined the comparative success of different design options to distill successful design patterns and other important lessons for the future developers of OSSM for personalized and social e-learning. Findings/Results The results confirmed the motivational impact of personalized social guidance provided by the OSSM system in the target context. The interface encouraged students to explore more topics and motivated them to work ahead of the course schedule. Both strong and weak students worked with the appropriate levels of questions for their readiness, which yielded consistent performance across different levels of complex problems. Additionally, providing more realistic content collection on the navigation-supported OSSM visualizations resulted in uniform performance for the group. Conclusions/Recommendation A sequence of studies of several OSSM interfaces confirmed that a combination of adaptive navigational support, open student modeling, and social visualization in the form of the OSSM interface can reinforce the navigational and motivational values of these approaches. In several contexts, the OSSM interface demonstrated its ability to offer effective guidance in helping students to locate the most relevant content at the right time while increasing student motivation to work with diverse learning content.

Open Student Models of Core Competencies at the Curriculum Level: Using Learning Analytics for Student Reflection

This paper proposes an approach for developing curriculum-level open student models. This approach entails evaluating student core competencies using the correspondence between courses and core competencies in a competency-based curriculum and students’ taken courses and grades. On the basis of this approach, a curriculum-level, competency-based visualized analytic system, called visualized analytics of core competencies (VACCs), was implemented. Course-competency diagnostic tools, course work performance radar charts, and peer-based ranking tables were developed as part of the VACC analytic system for student reflection and to position their levels of core competencies. These curriculum-level open student models revealed multiple aspects of students’ core competencies by monitoring the quantity and quality of courses taken by students, and evaluating students’ ranks regarding core competencies compared with their classmates and graduates. VACC evaluation was conducted in this paper. The results showed that more than 70% of students reported that VACC helped in reflecting on their core competencies, assisting them in understanding the correspondence between their taken courses and core competencies, and helping them to set goals regarding taking additional courses. In addition, this paper discusses potential analytics and applications of open student models of core competencies.

Open Social Student Modeling for Personalized Learning

Open student modeling (OSM) is an approach to technology-based learning, which makes student models available to the learners for exploration. OSM is known for its ability to increase student engagement, motivation, and knowledge reflection. A recent extension of OSM known as open social student modeling (OSSM) complements cognitive aspects of OSM with social aspects by allowing students to explore models of peer students and/or an aggregated class model. In this paper, we introduce an OSSM interface, MasteryGrids, and report the results of a large-scale classroom study, which explored the impact of the social dimension of OSSM. Students in a database management course accessed nonrequired learning materials (examples and problems) via the MasteryGrids interface using either OSM or OSSM. The results revealed that OSSM-enhanced learning, especially for students with lower prior knowledge, compared with OSM. It also enhanced user attitude and engagement. Amount of student usage, efficiency of student usage, and student attitude varied depending on the combination of interface condition (OSM/OSSM), gender, and student social comparison orientation.

Open Student Evaluation Model in e-Learning

This research paper aims to present an integrated evaluation model in e-learning systems for students. The paper describes the phases of development and analysis of the application of a web-based open student evaluation model in an e-Learning System. The proposed model has been tested and evaluated in terms of its effectiveness on student communication, collaboration, and progress. The evaluation has showed that the proposed model provides the students with flexible mechanism to control access to their model information.

Negotiation based adaptive learning sequences: Combining adaptivity and adaptability

This study proposes a negotiation-based approach to combine the notion of adaptivity (system-controlled adaptation) and adaptability (user-controlled adaptation) for an adaptive learning system. The system suggests adaptations and the student also submits his/her adaptation preference. When the student preference opposes the system suggestion, the student then negotiates with the system to reach an agreement of adaptation. A negotiation-based adaptive learning system (NALS) is implemented to support the generation of personalized adaptive learning sequences by system negotiations with students regarding assessments of learning performance (i.e. negotiated open student model) of the current content and choices of the next learning content (i.e. negotiation of adaptation). Students require two metacognitions in deciding adaptive learning sequences: self-assessment for evaluating their understanding of the current content and regulation for choosing appropriate learning content. Negotiated open student model are used for assist student self-assessment and negotiation of adaptation are used for assist student regulation of content choices. An experiment was conducted to compare a system-controlled adaptive learning system (SALS, adaptivity), a user-controlled adaptive learning system (UALS, adaptability), and a NALS. The results revealed that NALS promoted better metacognitions in student calibration (i.e. self-assessment) accuracy and learning content choices (i.e. regulation). Preliminary evidences also showed that NALS promoted better student performance in a delay test. The results further suggested that students with poor calibration accuracy and inappropriate content choices were not suitable to use UALS and were suitable to use SALS. The NALS can also be used for training students to make appropriate adaptation for learning.

A Software Suite for Efficient Use of the European Qualifications Framework in Online and Blended Courses

Since introduction of the European qualifications framework (EQF) as one instrument to bridge from learning institutions to competence driven lifelong learning, it remains a challenge for instructors and teachers in higher education to make efficient use of this framework for designing, monitoring, and managing their lessons. This paper presents a software suite for enabling teachers to make better use of EQF in their teaching. The software suite extends course design based on well-defined learning outcomes, monitoring performance and competence acquisition according to the EQF levels, assessment using scoring rubrics of EQF levels and competences in a 360-degree feedback, as well as visualizations of learning analytics and open student models in dashboards for different social perspectives in social planes. This paper includes a case study with 20 teachers who used the software suite in all phases of the course lifecycle for three programming courses. The results show that integrated applications for adopting the EQF in teaching practice are strongly needed. These results also show that the suite can assist teachers in creating contextual awareness, kindling reflection, understanding students and course progress, and inferring patterns of success and failure in competences development.

Progressor: social navigation support through open social student modeling

The increased volumes of online learning content have produced two problems: how to help students to find the most appropriate resources and how to engage them in using these resources. Personalized and social learning have been suggested as potential ways to address these problems. Our work presented in this paper combines the ideas of personalized and social learning in the context of educational hypermedia. We introduce Progressor, an innovative Web-based tool based on the concepts of social navigation and open student modeling that helps students to find the most relevant resources in a large collection of parameterized self-assessment questions on Java programming. We have evaluated Progressor in a semester-long classroom study, the results of which are presented in this paper. The study confirmed the impact of personalized social navigation support provided by the system in the target context. The interface encouraged students to explore more topics attempting more questions and achieving higher success rates in answering them. A deeper analysis of the social navigation support mechanism revealed that the top students successfully led the way to discovering most relevant resources by creating clear pathways for weaker students.

PRELIMINARY EVALUATION OF A NEGOTIABLE STUDENT MODEL IN A CONSTRAINT-BASED ITS

Previous research on adaptive educational systems has shown that allowing the student to view their student model is useful in the learning process. Open student models help support meta-cognitive processes, such as self-assessment and reflection, and at the same time increase the student's trust in the system. Negotiable student models take this a step further, and allow students to negotiate and potentially modify their model. Very few negotiable student models have been implemented, and only in relatively simple systems, not integrated into a complex Intelligent Tutoring System (ITS). Therefore, it is not clearly known whether negotiable student models pose a significant advantage over simpler open student models. This research implements a basic negotiable student model into a version of a complex and internationally deployed ITS. Subjective evaluation is performed, and shows promising results. Participants felt the negotiable student model was both useful for learning, and enjoyable to use. With a few improvements, this negotiable student model implementation could be used in a wide-scale objective analysis to help determine the usefulness of negotiable student models.

Evaluating the Effect of Open Student Models on Self-Assessment

This paper discusses the simple open student models used in two of our constraint-based tutors, SQL-Tutor and KERMIT, and their effects on self-assessment. The systems present a high-level abstract...