Marco Spruit, Ph.D., University Utrecht, Netherlands
He is an associate professor in the Information and Computing Sciences (ICS) department at the Faculty of Science of Utrecht University (UU) in The Netherlands. As principle investigator in the department’s Applied Data Science Lab, his research centres around Model-Driven Analytic Systems for Self-Service Data Science. He prominently participated in defining the new UU research focus area on Applied Data Science (ADS) and he is a member of UU’s Applied Data Science Education Committee as well as co-organiser of the ADS Special Interest Group on Text Mining. Research highlights include his team’s contributions to three Horizon2020 projects and two nationally funded projects on Analytic Systems. He has authored 150+ publications including 55+ journal papers. HIs ADS research team currently consists of 11 Ph.D students and 1 scientific programmer.
He acts as the programme coordinator for both the 90EC Applied Data Science for Health MSc postgraduate programme and the ADS 30EC master’s profile for both natural and life sciences students. Before 2016 he was the education manager of the Information Science BSc programme and member of the departmental Board of Examinations. In 2013 he participated in the Educational Leadership programme and has been awarded the Senior Teaching Qualification. Marco has recently also completed the Academic Leadership for Associate Professors programme.
Applied Data Science for Student Empowerment
The Applied Data Science Profile at Utrecht University
Data are everywhere. From the sciences to industry, commerce, and government, large collections of diverse data are becoming increasingly more indispensable for decision making, planning, and knowledge discovery. But how can we sensibly take advantage of all the opportunitities that these data potentially provide while avoiding the many pitfalls? The Master’s profile Applied Data Science at Utrecht University (UU) in The Netherlands addresses this challenge.
UU’s Applied Data Science is a multidisciplinary profile for students who are not only interested in broadening their knowledge and expertise within the field of Data Science, but are also eager to apply these capabilities in relevant projects within their research domain. Two mandatory courses provide a thorough introduction to data science, its basic methods, techniques, processes, and the application of data science within specific domains. The foundations of applied data science include relevant statistical methods, machine learning techniques and programming. Moreover, key aspects and implications of ethics, privacy and law are covered as well.
I zoom in on Data Science & Society, the introductory course for UU’s Applied Data Science profile, the Applied Data Science postgraduate MSc programme, and the Business Informatics (MBI) programme at Utrecht University. As such, this course’s primary objective is to inspire and introduce students to the emerging domain of Applied Data Science from a Big Data Technologies perspective, taking into account the entire knowledge discovery process and by applying selected big data technologies such as Hadoop and Spark to solve real-world problems to demonstrate the potential societal impact, in such a way that students feel empowered to confidently take on analytical tasks in the foreseeable future.
Tom Wambeke, Ph.D, International Training Centre of International Labour Organization, Turin, Italy
Tom Wambeke, Belgium, is graduated in Educational Sciences, holds a Master in Cultural Management and an Executive Business LEAD degree in Innovation at Stanford University.
Before joining the International Training Centre of the ILO he was assistant Professor at the University of Leuven and innovation coach at Open Higher Education.
He is currently Chief of Learning Innovation which specializes in providing sustainable learning solutions with the objective to generate impact and organizational change.
The unit he is leading has a double mandate: to strengthen the Centre’s in-house capacity to apply state-of-the art learning and knowledge sharing methods and technology, and to provide (e)-learning services to outside partners on a global scale. In this context he works closely together with UN agencies, development banks, international organ isations , governments and NGO’s.
As a certified international facilitator (IAF) he’s actively involved in strategy facilitation, participatory knowledge sharing, networked learning and ICT4Development. This he combines with a passion for complexity adaptive thinking, foresight analysis and futures exploration.
A deep dive into the Future. Exploring E-Learning scenario’s using Strategic Foresight.
Learning organisations and institutions need to adapt and evolve in an environment of continuous change. The problems of the future are unlikely to be solved solely by solutions that worked in the past. In this interactive and dynamic keynote presentation, a set of qualitative foresight methodologies and processes will be applied to emerging learning visions of the future beyond 2030. This keynote will not be about crystal ball gazing: all information comes from extensive horizon scanning and important education trends reports (Horizon, Gartner) and the presentation will apply foresight methods and techniques systematically to explore radical ideas about the alignment of (e)learning strategies with theories of what the future may have in store for us. Are you ready to be future proof?
Every participant of the conference will also receive free access to our Foresight toolkit to envision alternative futures in (e)learning.
Please download sli.do for interaction with Tom.
prof. Maurizio Gentile LUMSA University of Rome/Sapienza University Rome, Italy
Maurizio Gentile is Associate Professor of Teaching Methods and Special Education at LUMSA University of Rome and Professor of Technologies for Learning at Sapienza University of Rome. His research interests are Cooperative Learning, digital videos in teacher education, inclusive school, competency-based education, curriculum and assessment, technologies for learning. On these topics, more than 100 publications, including articles, book chapters, conference proceedings, monographs, editorials. He works with school network, research institutes, public educational organization, social organizations, editorial companies. From 2017 to 2018, he was Researcher in Experimental Educational Methods at Unitelma Sapienza University of Rome – the e-learning division of Sapienza University of Rome – and Instructional designer for the bachelor degree of Psychological Sciences and Techniques at Sapienza University of Rome.
Digital videos in teacher education: a professional vision model and four training strategies
The speech proposes a review of studies about the use of videotaping in teacher education. It deepens two issues: a) the construct of professional vision and sub-processes that teacher activates during the observation of videos; b) the formative approaches designed to develop the teachers’ competence to view a set of teaching actions.
The professional vision is the process of noticing noteworthy events and making sense of them. In this context, it is fascinating to investigate the relationship between general pedagogical knowledge and professional reasoning.
The speech examines four training strategies associated with using video in teacher education. The first strategy addresses to stimulate the interpretation of teaching events without a preliminary and formal knowledge of pedagogy underlying the observed teaching action (example-rule strategy). The experts recommend its use for in-service teacher training.
A second way addresses both the knowledge of educational principles and the development of decision-making abilities (rule-example strategy). The experts suggest its use in pre-service teacher education.
A third strategy is called “video club”. It consists of a group of teachers who meet to watch and discuss excerpts of videotapes of their instruction.
The last approach consists in one 20-hour course organised in three times: 1) three workshops, 2) the videotaping of teaching actions performed in the classrooms, 3) the shared analysis of videos. The research staff developed this strategy in the context of research provided for understanding and practising the assessment for learning approach. The aims of the project were: a) to design one in-service teacher education course based on digital videos; b) to study the interpretative frames that teachers activate when watching videos; c) to promote the assessment for learning approach. A group of 53 teachers was invited to participate in the project. The analysis of results is still ongoing.
Next keynotespeaker will be announced soon.