פרופ' ג'ודי קיי, סידני: מבינה מלאכותית ומדע נתונים בחינוך למערכות מידע אישיות ללומד

מכללת לוינסקי לחינוךהיא מוסד אקדמי ישראלי ותיק ומוביל, המעצב את פני החינוך והחברה ומציע השכלה גבוהה איכותית. מטרת המכללה היא טיפוח אנשי חינוך רגישים, חושבים, חוקרים, מובילים, יוזמים, יצירתיים, פעילים בקהילה ומנהיגים בסביבת עבודתם. מורים, אנשי חינוך ותומכי חינוך ימצאו בה בית ואפשרויות להתפתחות לאורך חייהם המקצועיים.

<H1 STYLE="text-align: right;">(ההרצאה באנגלית)</H1>
<H1>From OLMs + LAK + PI to PIL, Personal Informatics for Learners</H1>
This talk presents a vision for Personal Informatics for Learners (PIL). This builds on three foundations. The first, and oldest of these, comes from the decades of research on Open Learner Models (OLMs) in Artificial Intelligence in Education. These fields strive to create high quality teaching systems with personalisation driven by a fine-grained, carefully crafted model of the learner. The second is the far newer, but very fast growing LAK, Learning Analytics and Knowledge. This arose with wide deployment of learning technology that captures huge quantities of learning data and the tantalising possibilities such data offers. The third, Personal Informatics (PI) comes from Ubicomp research, aiming to harness personal sensor data about diverse aspects of life, particularly for health and wellness. PIL is grounded on the view that the learner should be empowered to take responsibility for their own learning. To achieve this, PIL needs to make progress on many fronts. We need mechanisms for collecting the right learning data and managing it effectively. We also need new classes of the interfaces and systems that enable learners to control their data, do personal data mining and engage in meta-cognitive processes of reflection, self-monitoring, planning.
The talk begins by reviewing the broad scope and vision described above. Taking that lens, I then present a two sets of case studies. The first relates to group-work, with interfaces onto data harvested as groups use an online collaboration tool or collaborate around an interactive tabletop or wall display, with diverse models, from the simple to richer ones built by data mining. Key insights come from the series of studies, both in the lab and in authentic classrooms.  The second set of case studies is for individual learning, ranging from mastering computer software and curriculum-wide learner modelling to personal informatics, for health and wellness, harnessing data from activity trackers, virtual reality and mobile food logging. The talk concludes with key lessons learnt and a research agenda for PIL.
<H2>Bio:</H2>
<A HREF="http://sydney.edu.au/engineering/it/%7Ejudy/" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">Judy Kay</A> is Professor of Computer Science. She leads the <A HREF="http://sydney.edu.au/engineering/it/%7Ehct/" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">Human Centred Technology Research Cluster</A>, in the Faculty of Engineering and IT at the University of Sydney and the <A HREF="http://www.cs.usyd.edu.au/%7Esitrg/" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">CHAI</A>, Computer Human Adapted Interaction, Research Group. Her research areas are in human computer interaction (HCI), ubiquitous computing (Ubicomp) and Artificial Intelligence in Education (AIED). A core focus of her research has been to create infrastructures, tools and interfaces for personalised lifelong life-wide learning. Central to this has been in the design of Open Learner Model interfaces that enable people to scrutinise and control the system's model of them and personalisation processes based on it. Her interface work has created the Cruiser Natural User Interaction (NIU) software which provides new ways for people to interact with interactive large surfaces, on tabletops and walls.  Her research has been commercialised and deployed and she has extensive publications in leading venues for research in AIED, human computer interaction and personalisation. She is co-Editor-in-Chief of the International Journal of Artificial Intelligence in Education.

חדר 118, מכללת לוינסקי לחינוך

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