(Lifelong) learning in your pocket?

Der Beitrag fokussiert die Entwicklung, den Einsatz und die Nutzung von innovativen Technologien zur Unterstützung von Bildungsszenarien in Schule, Hochschule und Weiterbildung. Ausgehend von den verschiedenen Phasen des Corporate Learning, Social Learning, Mobile Learning und Intelligent Learning wird in einem ersten Abschnitt das Nutzungsverhalten von Technologien durch Kinder, Jugendliche und (junge) Erwachsene in Schule, Studium und Lehre betrachtet. Es folgt die Darstellung technologischer Entwicklungen auf Basis des Technology Life Cycle und die Konsequenzen von unterschiedlichen Entwicklungszuständen und Reifegraden von Technologien wie Content Learning Management, sozialen Netzwerken, mobilen Endgeräten, multidimensionalen und -modalen Räumen bis hin zu Anwendungen augmentierter Realität und des Internets der Dinge, Dienste und Daten für den Einsatz und die Nutzung in Bildungsszenarien. Nach der Darstellung von Anforderungen an digitale Technologien hinsichtlich Inhalte, Didaktik und Methodik wie etwa hinsichtlich der Erstellung von Inhalten, deren Wiederverwendung, Digitalisierung und Auffindbarkeit sowie Standards werden methodische Hinweise zur Nutzung digitaler Technologien zur Interaktion von Lernenden, von Lehrenden, sozialer Interaktion, kollaborativem Autorieren, Kommentierung, Evaluation und Begutachtung gegeben. Abschließend werden - differenziert für Schule und Hochschule - Erkenntnisse zu Rahmenbedingungen, Einflussgrößen, hemmenden und fördernden Faktoren sowie Herausförderungen bei der Einführung und nachhaltigen Implementation digitaler Technologien im schulischen Unterricht, in Lehre, Studium und Weiterbildung im Überblick zusammengefasst.

Using automated text analysis to evaluate students’ conceptual understanding

Background: A major challenge for assessing students’ conceptual understanding of STEM subjects is the capacity of assessment tools to reliably and robustly evaluate student thinking and reasoning. Multiple-choice tests are typically used to assess student learning and are designed to include distractors that can indicate students’ incomplete understanding of a topic or concept based on which distractor the student selects. However, these tests fail to provide the critical information uncovering the how and why of students’ reasoning for their multiple-choice selections. Open-ended or structured response questions are one method for capturing higher level thinking, but are often costly in terms of time and attention to properly assess student responses. Purpose: The goal of this study is to evaluate methods for automatically assessing open-ended responses, e.g. students’ written explanations and reasoning for multiple-choice selections. Design/Method: We incorporated an open response component for an online signals and systems multiple-choice test to capture written explanations of students’ selections. The effectiveness of an automated approach for identifying and assessing student conceptual understanding was evaluated by comparing results of lexical analysis software packages (Leximancer and NVivo) to expert human analysis of student responses. In order to understand and delineate the process for effectively analysing text provided by students, the researchers evaluated strengths and weakness for both the human and automated approaches. Results: Human and automated analyses revealed both correct and incorrect associations for certain conceptual areas. For some questions, that were not anticipated or included in the distractor selections, showing how multiple-choice questions alone fail to capture the comprehensive picture of student understanding. The comparison of textual analysis methods revealed the capability of automated lexical analysis software to assist in the identification of concepts and their relationships for large textual data sets. We also identified several challenges to using automated analysis as well as the manual and computer-assisted analysis. Conclusions: This study highlighted the usefulness incorporating and analysing students’ reasoning or explanations in understanding how students think about certain conceptual ideas. The ultimate value of automating the evaluation of written explanations is that it can be applied more frequently and at various stages of instruction to formatively evaluate conceptual understanding and engage students in reflective

Who are our repeating students? Profiling students persisting after failure

Research on attrition has focused on the economic significance of low graduation rates in terms of costs to students (fees that do not culminate in a credential) and impact on future income. For a student who fails a unit and repeats the unit multiple times, the financial impact is significant and lasting (Bexley, Daroesman, Arkoudis & James 2013). There are obvious advantages for the timely completion of a degree, both for the student and the institution. Advantages to students include fee minimisation, enhanced engagement opportunities, effectual pathway to employment and a sense of worth, morale and cohort-identity benefits. Work undertaken by the QUT Analytics Project in 2013 and 2014 explored student engagement patterns capturing a variety of data sources and specifically, the use of LMS amongst students in 804 undergraduate units in one semester. Units with high failure rates were given further attention and it was found that students who were repeating a unit were less likely to pass the unit than students attempting it for the first time. In this repeating cohort, academic and behavioural variables were consistently more significant in the modelling than were any demographic variables, indicating that a student’s performance at university is far more impacted by what they do once they arrive than it is by where they come from. The aim of this poster session is to examine the findings and commonalities of a number of case studies that articulated the engagement activities of repeating students (which included collating data from Individual Unit Reports, academic and peer advising programs and engagement with virtual learning resources). Understanding the profile of the repeating student cohort is therefore as important as considering the characteristics of successful students so that the institution might be better placed to target the repeating students and make proactive interventions as early as possible.

Education and the relation to the outside: A little real reality

One of the aims of Deleuze. Guattari. Schizoanalysis. Education. is to focus on the radical reconfiguration that education is undergoing, impacting educator, administrator, institution and ‘sector’ alike. More to the point, it is the responses to that process of reconfiguration - this newly emerging assemblage - that are a key focal point in this issue. Essential to these responses, we propose, is Deleuze and Guattari’s method of schizonalysis, which offers a way to not only understand the rules of this new game, but also, hopefully, some escape from the promise of a brave new world of continuous education and motivation. A brave new world of digitised courses, impersonal and corporate expertise, updatable performance metrics, Massive Open Online Courses (MOOCs), learning analytics, transformative teaching and learning, online high-stakes testing in the name of transforming and augmenting human capital overlays the corporeal practices of institutional surveillance, examination and categorical sorting. A brave new world, importantly, where people’s continuous education is instituted less, or not simply, through disciplinary practices, and increasingly through a constant and continuous sampling and profiling of not simply performance but their activity, measured against the profiled activity of a ‘like’ age group, person, or an institution. This continuous education, including the sampling that accompanies it, we are all informed through various information and marketing campaigns, is in our best interest. An interest that is driven and governed by an ever-increasing corporatisation and monetisation of ‘the knowledge sector’, as well as an interest that is sustained through an ever-increasing, as well as continuous, debt.

Towards automated content analysis of discussion transcripts: A cognitive presence case

In this paper, we present the results of an exploratory study that examined the problem of automating content analysis of student online discussion transcripts. We looked at the problem of coding discussion transcripts for the levels of cognitive presence, one of the three main constructs in the Community of Inquiry (CoI) model of distance education. Using Coh-Metrix and LIWC features, together with a set of custom features developed to capture discussion context, we developed a random forest classification system that achieved 70.3% classification accuracy and 0.63 Cohen's kappa, which is significantly higher than values reported in the previous studies. Besides improvement in classification accuracy, the developed system is also less sensitive to overfitting as it uses only 205 classification features, which is around 100 times less features than in similar systems based on bag-of-words features. We also provide an overview of the classification features most indicative of the different phases of cognitive presence that gives an additional insights into the nature of cognitive presence learning cycle. Overall, our results show great potential of the proposed approach, with an added benefit of providing further characterization of the cognitive presence coding scheme.

Chapter 2: Predicting Newcomer Integration in Online Knowledge Communities by Automated Dialog Analysis

Nistor, N., Dascalu, M., Stavarache, L.L., Tarnai, C., & Trausan-Matu, S. (2015). Predicting Newcomer Integration in Online Knowledge Communities by Automated Dialog Analysis. In Y. Li, M. Chang, M. Kravcik, E. Popescu, R. Huang, Kinshuk & N.-S. Chen (Eds.), State-of-the-Art and Future Directions of Smart Learning (Vol. Lecture Notes in Educational Technology, pp. 13–17). Berlin, Germany: Springer-Verlag Singapur

Visualization of polyphonic voices inter-animation in CSCL chats

Trausan-Matu, S., & Dascalu, M. (2015). Visualization of Polyphonic Voices Inter-animation in CSCL Chats. Revista Romana de Interactiune Om-Calculator, 8(4), 305–322.

ReaderBench: Automated evaluation of collaboration based on cohesion and dialogism

Dascalu, M., Trausan-Matu, S., McNamara, D.S., & Dessus, P. (2015). ReaderBench – Automated Evaluation of Collaboration based on Cohesion and Dialogism. International Journal of Computer-Supported Collaborative Learning, 10(4), 395–423. doi: 10.1007/s11412-015-9226-y

The development and implementation of math projects in a HEI: expectations, objectives, experiences and analysis

An overwhelming problem in Math Curriculums in Higher Education Institutions (HEI), we are daily facing in the last decade, is the substantial differences in Math background of our students. When you try to transmit, engage and teach subjects/contents that your “audience” is unable to respond to and/or even understand what we are trying to convey, it is somehow frustrating. In this sense, the Math projects and other didactic strategies, developed through Learning Management System Moodle, which include an array of activities that combine higher order thinking skills with math subjects and technology, for students of HE, appear as remedial but important, proactive and innovative measures in order to face and try to overcome these considerable problems. In this paper we will present some of these strategies, developed in some organic units of the Polytechnic Institute of Porto (IPP). But, how “fruitful” are the endless number of hours teachers spent in developing and implementing these platforms? Do students react to them as we would expect? Do they embrace this opportunity to overcome their difficulties? How do they use/interact individually with LMS platforms? Can this environment that provides the teacher with many interesting tools to improve the teaching – learning process, encourages students to reinforce their abilities and knowledge? In what way do they use each available material – videos, interactive tasks, texts, among others? What is the best way to assess student’s performance in these online learning environments? Learning Analytics tools provides us a huge amount of data, but how can we extract “good” and helpful information from them? These and many other questions still remain unanswered but we look forward to get some help in, at least, “get some drafts” for them because we feel that this “learning analysis”, that tackles the path from the objectives to the actual results, is perhaps the only way we have to move forward in the “best” learning and teaching direction.

Big Data: Wrongs and Rights by Andrew Cormack (WAIS Seminar)

Abstract: Big Data has been characterised as a great economic opportunity and a massive threat to privacy. Both may be correct: the same technology can indeed be used in ways that are highly beneficial and those that are ethically intolerable, maybe even simultaneously. Using examples of how Big Data might be used in education - normally referred to as "learning analytics" - the seminar will discuss possible ethical and legal frameworks for Big Data, and how these might guide the development of technologies, processes and policies that can deliver the benefits of Big Data without the nightmares. Speaker Biography: Andrew Cormack is Chief Regulatory Adviser, Jisc Technologies. He joined the company in 1999 as head of the JANET-CERT and EuroCERT incident response teams. In his current role he concentrates on the security, policy and regulatory issues around the network and services that Janet provides to its customer universities and colleges. Previously he worked for Cardiff University running web and email services, and for NERC's Shipboard Computer Group. He has degrees in Mathematics, Humanities and Law.

Assessing the suitability of student interactions from Moodle data logs as predictors of cross-curricular competencies

In the past decades, online learning has transformed the educational landscape with the emergence of new ways to learn. This fact, together with recent changes in educational policy in Europe aiming to facilitate the incorporation of graduate students to the labor market, has provoked a shift on the delivery of instruction and on the role played by teachers and students, stressing the need for development of both basic and cross-curricular competencies. In parallel, the last years have witnessed the emergence of new educational disciplines that can take advantage of the information retrieved by technology-based online education in order to improve instruction, such as learning analytics. This study explores the applicability of learning analytics for prediction of development of two cross-curricular competencies – teamwork and commitment – based on the analysis of Moodle interaction data logs in a Master’s Degree program at Universidad a Distancia de Madrid (UDIMA) where the students were education professionals. The results from the study question the suitability of a general interaction-based approach and show no relation between online activity indicators and teamwork and commitment acquisition. The discussion of results includes multiple recommendations for further research on this topic.

A IMPORTÂNCIA DAS TICS E DA EDUCAÇÃO COMO PROCESSO COMUNICACIONAL DIALÓGICO NO ENSINO SUPERIOR: Um Estudo da Universidade Estadual de Mato Grosso do Sul

Esta tese teve por objetivo saber como o corpo docente da Universidade Estadual de Mato Grosso do Sul (UEMS) percebe, entende e reage ante a incorporação e utilização das Tecnologias de Informação e Comunicação (TICs) nos cursos de graduação dessa Instituição, considerando os novos processos comunicacionais dialógicos que elas podem proporcionar na sociedade atual. Metodologicamente, a tese é composta por pesquisa bibliográfica, buscando fundamentar as áreas da Educação e Comunicação, assim como a Educomunicação; pesquisa documental para contextualização do lócus da pesquisa e de uma pesquisa exploratória a partir da aplicação de um questionário online a 165 docentes da UEMS, que responderam voluntariamente. Verificou-se que os professores utilizam as TICs cotidianamente nas atividades pessoais e, em menor escala, nos ambientes profissionais. Os desafios estão em se formar melhor esse docente e oferecer capacitação continuada para que utilizem de forma mais eficaz as TICs nas salas de aula. Destaca-se ainda que os avanços em tecnologia e os novos ecossistemas comunicacionais construíram novas e outras realidades, tornando a aprendizagem um fator não linear, exigindo-se revisão nos projetos pedagógicos na educação superior para que estes viabilizem diálogos propositivos entre a comunicação e a educação. A infraestrutura institucional para as TICs é outro entrave apontado, tanto na aquisição como na manutenção desses aparatos tecnológicos pela Universidade. Ao final, propõe-se realizar estudos e pesquisas que possam discutir alterações nos regimes contratuais de trabalho dos docentes, uma vez que, para atuar com as TICs de maneira apropriada, exige-se mais tempo e dedicação do docente.

Big Data – Opportunities and Challenges for Education

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2015

Finding the Needle in a Haystack: Who are the Most Central Authors Within a Domain?

The speed at which new scientific papers are published has increased dramatically, while the process of tracking the most recent publications having a high impact has become more and more cumbersome. In order to support learners and researchers in retrieving relevant articles and identifying the most central researchers within a domain, we propose a novel 2-mode multilayered graph derived from Cohesion Network Analysis (CNA). The resulting extended CNA graph integrates both authors and papers, as well as three principal link types: coauthorship, co-citation, and semantic similarity among the contents of the papers. Our rankings do not rely on the number of published documents, but on their global impact based on links between authors, citations, and semantic relatedness to similar articles. As a preliminary validation, we have built a network based on the 2013 LAK dataset in order to reveal the most central authors within the emerging Learning Analytics domain.