Educational Repositories Research Articles

Introducing BRAINOER: The Behavioral Research and Interdisciplinary Neuroscience Open Educational Repository.

Foundational textbooks for neuroscience courses can be cost-prohibitive for students and may omit recent advances in the field. Therefore, an Open Educational Resource (OER) repository was curated using existing OER materials for use in behavioral neuroscience and physiology courses. The Behavioral Research and Interdisciplinary Neuroscience Open Educational Repository (BRAINOER) contains 9 modules that include the following foundational topics: (1) The Brain and Nervous System, (2) Neurons, (3) The Endocrine System, (4) Neurotransmitters and Psychopharmacology, (5) Motor Processing, (6) Advanced Brain Functions, (7) Sensation and Perception, (8) Genetics and Evolution, (9) Research, Design, and Methods. Each module contains learning objectives in a checklist format, and modules are divided into basic and advanced content where appropriate. Because the repository is divided into content modules, the materials can be used as a full-curriculum or assigned on a module-by-module basis.

Multicultural online science resources: exploring preservice teachers’ perspectives

PurposeCurriculum supplementation by teachers is an agelong tradition, and the widespread use of the internet has increased the use of online resources in the classroom. This paper aims to explore preservice teachers’ views on multicultural science resources and make a case for the representation of the changing demographics of the American classroom in online resource development.Design/methodology/approachUsing a qualitative interpretive approach, this study explored the perceptions of preservice teachers on their access to and use of online science resources through the conceptual lens of the pedagogical design capacity framework (Brown, 2009) and the first two principles of critical and cultural approaches to ambitious science teaching (C2AST) (Thompson et al., 2021).FindingsParticipants in this study have not accessed culturally relevant online science resources. They adapt the resources to meet the demographic needs of their class.Practical implicationsThis study aims to support the need for content creators of online educational repositories to develop multicultural science resources.Originality/valueThis work not only gives a background to why preservice early childhood science teachers could not access multicultural online resources, but it also makes a case for integrating skills needed for teachers to create culturally relevant resources into teacher training programs.

Doctoral Teaching and Mentoring in Digital Humanities: Changing Approaches to Graduate Pedagogy in Times of Multiple Crises

Focusing on graduate student education and professional development in the humanities, we examine how crises of the last few years – COVID-19, precarious employment and racial reckoning, among others – exposed iniquities in digital humanities (DH) and pedagogical training. This article explores how Emory Center for Digital Scholarship’s (ECDS) outreach initiatives operated through and responded to recent years’ crises post-2020. ECDS is committed to creating equitable opportunities for DH and pedagogical training for graduate students through long-term training, six-week intensives and an evolving open educational repository. The Digital Scholarship Training Program (DSTP) is a paid training programme for graduate students to learn digital skills through project-based learning. For students who cannot commit to a long-term practicum, ECDS offers two six-week intensives to provide equal opportunities for pedagogical training with emphasis on digital methods and tools. Currently, ECDS is building a repository hosted on WordPress to provide more flexible graduate training opportunities. By attuning ECDS offerings to varying levels of time and access, this suite of options aims to create equitable opportunities for graduate professional development that could serve as examples for other institutions. We conclude that DH methods and modalities can be deployed effectively to help address gaps in graduate student training.

Proposal of Pedagogical Medical Record Under the Perspective of the Individualized Education Plan (IPE)

Individualized Educational Plan (PEI) is characterized by being an instrument that mediates learning, allowing a systematic evaluation of teaching. From this perspective, based on the Operationalized Portage Inventory – IPO – and the PEI, the creation of the Individualized Educational Repository was inspired, a digital folder shared between the teacher, family and other professionals involved with the learning of children with Autistic Spectrum Disorder (ASD). in Early Childhood Education, creating a place to record the collection of evaluated items and integration of monitored data, in the short, medium and long term. That said, this article aims to describe a proposal for a pedagogical record, under the bias of the PEI, using bibliographical research as a methodology, based on the theoretical assumptions of Vygotsky (2008); Tannús-Valadão (2018); Glat, Vianna, Redig (2012), among others. It is hoped that the implementation of this tool will provide teachers with a differentiated and continuous way of monitoring learning, contemplating the evaluation of the areas of socialization, language, cognition, self-care and motor development, for children from 0 to 6 years old.

Feasibility study on the Development of Higher Education Repository X in Pagar Alam, South Sumatra

Higher education is an institution that has various sections and work units that work together in carrying out the Tri Dharma principles, namely research, learning and service, which are able to accommodate large amounts of data, both in conventional and digital forms. digitally it is called a repository, college x in Pagar Alam, South Sumatra does not yet have a repository, so a feasibility study must be carried out which can later become a forum for suggestions. Before the repository is developed, a feasibility study must be carried out so that the development can be carried out properly. This feasibility study is first carried out through the management life cycle, where this research includes survey method re- search. This research produces data from an infrastructure feasibility study in building a repository for Higher Education x in Pagar Alam, South Sumatra, which is 80%, this percentage is obtained from infrastructure feasibility 40%, HR 10%, Budget 0%, SPMI (SOP/SK) of 10 %, and 20% repository content. The things that need to be fixed are the availability and addition of IT infrastructure, software, additional rules (SOP), and procedures for submitting and uploading data.

Produção científica sobre repositórios de recursos educacionais abertos no ensino superior em bases de dados

Within the scope of the open access movement, educational repository initiatives arise that propose the availability of open educational resources to support teaching and research activities, which requires studies to understand the modus operandi of educational repositories. In this sense, the aim of this study is to analyze the scientific production on repositories of open educational resources aimed at higher education, in the scientific literature, seeking to identify research trends and the aspects that should be considered in the development of an educational repository. The methodology is based on a bibliometric study on the Scopus and Web of Science bases and uses the qualitative approach to content analysis of 89 scientific publications. The results indicate that technological and technical aspects, including metadata, interoperability, use licenses, quality assurance, semantic web, recommendation systems and social and collaborative tools, in addition to pedagogical ones, tend to guide the studies on educational repositories, expanding the possibilities for their development. From this study, it is expected to contribute with new knowledge that can stimulate national scientific production and promote the advancement of knowledge in this theme, in addition to contributing to good practices in the management of open educational resources.

Soft Skills and Graduate Employability: Evidence from Malaysian Tracer Study

Recent trends in graduate employment have raised concerns among higher education providers and other stakeholders. Issues concerning the soft skills gap have been constantly raised so that industries and universities can adopt various initiatives to address this situation. In addition, employment has shifted from production to service, increasing the importance of soft skills. This study aims to map graduates’ soft skills and employment status after graduation. The Ministry of Higher Education repository was used to select 100,413 first-degree graduates who had completed their studies. Logistic regression analysis created the graduate employability predictive model, which yielded a 77% accuracy. The findings show that 85.5% of graduates were employed during data collection. The predictive model suggests that graduate employability status is affected by factors such as gender, family income, the field of study, MUET, CGPA, internship, entrepreneurship course, working experience, communication skills, analytical skills, teamwork, positive values, and general knowledge.

Open Educational Repository Produces Licensed Resources to Sustain Project

The Neuro-Ophthalmology Virtual Education library (NOVEL) is a partnership between the Spencer S. Eccles Health Sciences Library (EHSL) at the University of Utah and the North American Neuro-Ophthalmology Society (NANOS) that resulted in a peer reviewed digital collection of educational publications, journal articles, conference proceedings, a patient portal, and an illustrated curriculum of neuro-ophthalmology resources. This unique and innovative collaboration has evolved and expanded for more than 18 years. The partnership takes advantage of the strengths of each organization and combines them to create valuable scholarly products that support education and research in neuro-ophthalmology.

Investigating the necessity of having digital repositories in postbasic education in Oman

Investigating the necessity of having digital repositories in postbasic education in Oman

Old but Not Old Fashioned: Agricultural Landscapes as European Heritage and Basis for Sustainable Multifunctional Farming to Earn a Living

Today, farmers are multioptional entrepreneurs, demanding far more skills than only those of agricultural production. The awareness of European agricultural landscape (EAL) values should enable farmers to create new business strategies. Open education repositories (OERs) based on online vocational education and training (VET) are still not widespread. The project FEAL (multifunctional farming for the sustainability of EALs) has brought interactive material online based on results of two questionnaire surveys performed in Germany, Italy, Slovakia, Slovenia, and Spain. A survey of 31 experts confirmed that VET activities are very much needed for farmers. A survey of 28 farmers had different aims and content. Data collected from farmers were used to evaluate basic farm attributes, farmers’ characteristics, and keywords indicating the farms’ activities, multifunctionality and sustainability, and EALs, specifying the presence of nature- and landscape-protected areas. A decision-making schema, applying a collection of terms from literature analysis and the questionnaire’s results, is a support tool to develop a model of a farm that contributes to the preservation of the landscape’s character, strengthening the landscape’s quality, and sustainable business. The model presents the interactions of the farm (its territory and ancestral heritage, control of natural resources, tourism services and cultural events, public goods provision, and quality guarantees); socioeconomic strategies regarding quality, marketing, communication, business operation, and monitoring are proposed.

Teaching Cheminformatics through a Collaborative Intercollegiate Online Chemistry Course (OLCC).

While cheminformatics skills necessary for dealing with an ever-increasing amount of chemical information are considered important for students pursuing STEM careers in the age of big data, many schools do not offer a cheminformatics course or alternative training opportunities. This paper presents the Cheminformatics Online Chemistry Course (OLCC), which is organized and run by the Committee on Computers in Chemical Education (CCCE) of the American Chemical Society (ACS)’s Division of Chemical Education (CHED). The Cheminformatics OLCC is a highly collaborative teaching project involving instructors at multiple schools who teamed up with external chemical information experts recruited across sectors, including government and industry. From 2015 to 2019, three Cheminformatics OLCCs were offered. In each program, the instructors at participating schools would meet face-to-face with the students of a class, while external content experts engaged through online discussions across campuses with both the instructors and students. All the material created in the course has been made available at the open education repositories of LibreTexts and CCCE Web sites for other institutions to adapt to their future needs.

Engaging Undergraduate Public Health Students Through a Textbook Creation Project

This study examines students’ perceptions of an open pedagogy experiment in which they created their own textbook for an undergraduate public health course. The lead author’s primary motivation for developing this assignment was the high cost associated with the traditional textbooks that were otherwise needed to cover the breadth of subject matter in the course. The resulting open textbook included 19 chapters, covering all the required components of the course, and the final version was published in a statewide open educational resource repository. Students provided feedback about this undertaking by way of an end-of-term survey. The results showed high percentages of students who associated the textbook creation project with greater engagement and satisfaction than the passive use of traditional textbooks. Students also reported their perception of a learning benefit related to the creation of course content. Pedagogical implications of this study are discussed, and future research questions are proposed.

Comparative Analytics and Predictive Modeling of Student Performance through Data Mining Techniques

As a matter of fact Data Mining is increasingly used as an emerging research domain in educational fields as well for extracting useful and previously unknown patterns from educational repositories. This research is an attempt to predicting the performance of the students for improving it in future through experimental analysis and predictive modeling. This experimental analysis and predictive modeling in learning process of students can be used as a better instrumental. In this study it was perceived that educational repositories/databases can have sufficient facts about learning attitude and capability etc. These factors are required to be understood for discovery of new hidden patterns and knowledge. These hidden patterns and knowledge can be later used for performance enhancement of the students through strategic planning and proper action by the university/college authorities. Researcher observed that there is lack of predictive studies and models available in Ethiopian context to accurately determine the influencing factors of the students’ performance in academics by categorizing student status in to drop out/fail, poor, good, excellent, or an average performer. Researcher also observed that there are many factors that affects student’ performance in university level education and some of selected factors in this research study are Gender, Department, Course, and Credit hours etc. Many educational institutions have still no enough strategic plan to predict or determine the student performance in order to improve it, reduce drop out and help to implement the curriculum / academic policies based on student performance and status. This research aims to conduct a comparative analysis and predictive modeling for knowing the student performance status through data mining techniques so as to improve their performance and status. This study used the KDD process model to find and interpret patterns in respositories. Decision tree (J48 and Random Forest), Bayes (NaiveBayes and BayesNet) and Rule Based (JRip and PART) algorithms are used for classification. The result of this study reveals that overall accuracy of the tested classifiers is above 80%. In addition, classification accuracy for the different classes reveals that the predictions are worst for fail class and fairly good for the average class. The J48 and JRip classifiers relatively produces highest classification accuracy for the average performer/ status. Finally the study suggests that data mining can be used as significant technique to figure out student performance based on salient factors affecting.

An automated learning content classification model for open education repositories: Case of MERLOT II

The value of OERs mainly depends on how easy they can be searched or located through a web search engine. Currently, the MERLOT II metadata repository requests resource providers to choose the relevant discipline category manually while adding material to its repository. This practice appears very time-consuming and also bound to involve human errors. If a member picks an incorrect discipline category, then the learning resource may not be correctly categorized in the repository. This situation may result in a learning resource to be not shortlisted for a given keyword search of the “MERLOT Smart Search” or in the “Advanced search.” Above investigations motivated us to recognize the importance of developing an automated learning content classification solution for OER repositories. In this study, we proposed a novel automated learning content classification model (LCCM) to classify learning resources into relevant discipline categories while adding them to the MERLOT repository. The research goal incorporated in this paper include dataset preparation, data preprocessing, feature extraction using LDA topic model, and calculating the semantic similarity using a pre-trained word embedding matrix. These methods serve as a base for classifying learning resources more effectively within a short time.

CONSORTIUM IN EDUCATION: DIVERSIFICATION PROCESSES AND ADVANCED TRAINING MODELS IN EDUCATIONAL MANAGEMENT AND FOR PEDAGOGICAL AND SCIENTIFIC-PEDAGOGICAL WORKERS

Resume. Global social shifts are requiring qualitative growth of staffing education at all levels. In the period of changes, the system of certification training and postgraduate education of managerial, pedagogical and scientific-pedagogical workers of the branch identified as a priority in implementing innovative approaches to the formation of a new generation of educators, development of new strategies, forms, the content of their professional growth. The study proposes to consider diversification of advanced training for education workers at all levels using the consortium resource as a new institutional form of an educational organization. The effectiveness of the proposed model in ensuring the systematic coordination of inter-institutional cooperation in the fields of academic mobility, research, technological development, and innovation, enhancing the competitiveness of national education at the international level had been proved. Following the example of the activities of the Consortium of Postgraduate Education Institutions and the Ukrainian Open University of Postgraduate Education new opportunities for the qualitative development of postgraduate education have been opened. These opportunities are sharing open educational technologies, resources, and repositories, creating new models of collaboration to develop and disseminate educational resources, the purpose of which is to ensure the quality of education and to implement educational activities based on new technology, didactics and the organization of training. The basic directions and models of innovative approach are analysed for education workers training at all education levels in the context of sustainable development goals, the need for diversification of professional development of pedagogical, scientifically pedagogical and managerial education workers in the context of multi-vector interaction of educational institutions through a consortium is investigated and substantiated. It is proved that the introduction of diversified models of institutional organization of education in the digital society is a crucial component of the continuity of professional development of management, pedagogical and scientific-pedagogical workers and education as a whole.

Web Service to Retrieve and Semantically Enrich Datasets for Theses From Open Educational Repositories

The paper describes the design and implementation of a semantic web service that retrieves theses and extends the keyword based-search of a DSpace repository taking into account the roles of advisors and steering committee members formally represented into a custom-made ontology. The service uses SPARQL queries and the serialization module of RDF DSpace, this links the item submission process and the ontology, thus the more theses are added into a repository, the more instances are inserted into the ontology. The paper provides empirical insights about how to reuse theses metadata and includes the results of an exploratory and self-management survey of usability heuristic evaluation of a web site that enables to access the proposed service. Heuristics were estimated with a purposive sample of students, teachers, and managers, the results indicated a high satisfaction level and showed that the service increased theses accessibility in the web environment. The service also generates semantically enriched datasets that coexist with the repository, they are of utility and value to educational organizations as they give institutional visibility.

Semantic annotation and harvesting of federated scholarly data using ontologies

PurposeEffective synthesis of learning material is a multidimensional problem, which often relies on handpicking approaches and human expertise. Sources of educational content exist in a variety of forms, each offering proprietary metadata information and search facilities. This paper aims to show that it is possible to harvest scholarly resources from various repositories of open educational resources (OERs) in a federated manner. In addition, their subject can be automatically annotated using ontology inference and standard thematic terminologies.Design/methodology/approachBased on a semantic interpretation of their metadata, authors can align external collections and maintain them in a shared knowledge pool known as the Learning Object Ontology Repository (LOOR). The author leverages the LOOR and show that it is possible to search through various educational repositories’ metadata and amalgamate their semantics into a common learning object (LO) ontology. The author then proceeds with automatic subject classification of LOs using keyword expansion and referencing standard taxonomic vocabularies for thematic classification, expressed in SKOS.FindingsThe approach for automatic subject classification simply takes advantage of the implicit information in the searching and selection process and combines them with expert knowledge in the domain of reference (SKOS thesauri). This is shown to improve recall by a considerable factor, while precision remains unaffected.Originality/valueTo the best of the author’s knowledge, the idea of subject classification of LOs through the reuse of search query terms combined with SKOS-based matching and expansion has not been investigated before in a federated scholarly setting.

Getting Value from Open Educational Repositories

This article was migrated. The article was not marked as recommended. Open Educational Repositories (OERs) have not seen the wide adoption that was predicted when they were introduced. A number of factors contribute to this but in this article, we explore some new tools and mechanisms that will create additional value from their use, for contributors, learners and organizations.

NOVICE TEACHERS USE OF ICT FOR TEACHING PURPOSES AT SECONDARY SCHOOL LEVEL

Social, economic and technological development of a nation depends a lot on the use of ICT. The key objective is to analyze novice teachers' use of ICT for teaching purposes. Teachers realized that ICT tools are very helpful and supporting to help students in sharing and creating information through technological devices over computer systems and webs. Novice secondary school teachers who taught to 9th and 10th classes were the population of the current study. Researchers selected 200 novice secondary school teachers as sample. Simple random sampling technique was used for the selection of sample. Researchers used questionnaire as data collection tool. The questionnaire was administered to the sample of the study. The most suitable statistical techniques of frequency, percentage, mean score and standard deviation. In the light of findings this research study shows that the use of ICT gadgets and other resources help for effective teaching at secondary school level. The institution has internet facility to support teaching. The study concluded that the use of ICT is helpful in getting awareness about teaching practices and access to related content. In current decade, ICT is rapidly revolutionizing the ICT use in collaborative learning within the premises of educational institutions and at home. It is also concluded that novice secondary school teachers are making the use of educational repositories for academic purposes.

A multilevel logistic hidden Markov model for learning under cognitive diagnosis.

Students who wish to learn a specific skill have increasing access to a growing number of online courses and open-source educational repositories of instructional tools, including videos, slides, and exercises. Navigating these tools is time-consuming and the search itself can hinder the learning of the skill. Educators are hence interested in aiding students by selecting the optimal content sequence for individual learners, specifically which skill one should learn next and which material one should use to study. Such adaptive selection would rely on pre-knowledge of how the learners' and the instructional tools' characteristics jointly affect the probability of acquiring a certain skill. Building upon previous research on Latent Transition Analysis and Learning Trajectories, we propose a multilevel logistic hidden Markov model for learning based on cognitive diagnosis models, where the probability that a learner acquires the target skill depends not only on the general difficulty of the skill and the learner's mastery of other skills in the curriculum but also on the effectiveness of the particular learning tool and its interaction with mastery of other skills, captured by random slopes and intercepts for each learning tool. A Bayesian modeling framework and an MCMC algorithm for parameter estimation are proposed and evaluated using a simulation study.