LSAC 2018: Learning and Student Analytics Conference 2018 University of Amsterdam Amsterdam, Netherlands, October 22-23, 2018 |
Conference website | http://lsac2018.org |
Submission link | https://easychair.org/conferences/?conf=lsac2018 |
Conference registration starts | May 15, 2018 |
Submission deadline | August 1, 2018 |
Notification of acceptance | August 31, 2018 |
2nd Annual Learning & Student Analytics Conference
Deploying Artificial Intelligence to Improve Learning while Ensuring Privacy
#LSAC2018
University of Amsterdam
TIB Hannover
Vrije Universiteit Amsterdam
SURF
Conference Venue:
October 22-23, 2018
Location: REC-A Building, Nieuwe Achtergracht 166,
1018 WV Amsterdam, The Netherlands
The aim of the Learning & Student Analytics Conference (LSAC) 2018 is to bring together researchers and practitioners from a number of disciplines (e.g. education, artificial technology, computer science, management, psychology, economics, IT security), organisational and national policy makers, educational practitioners, students, and employers, to share and discuss the latest research insights related to Learning Analytics. The conference further provides a platform for stakeholders to engage in critical conversations about current trends and policy requirements.
This year the conference programme will give particular attention to learning practices, emerging themes, and case studies centered around Artificial Intelligence (AI). Therefore academics and practitioners alike, who are interested in topics such as self-regulated learning, the incorporation into the domain of learning analytics of novel data sources (e.g., job market data or social media), privacy and ethics, and data security, should consider submitting an abstract and attending this event.
Artificial Intelligence (AI) has been identified as a disruptive force that will impact many areas of society, including education. Indeed, AI will impact every aspect across all sectors of education, ranging from pedagogy, teaching, and learning, to curriculum design or from traditional curriculum based formal education to highly personalized informal learning approaches. Involving researchers, educators, and policy makers in enabling valid, reliable, and ethical AI driven educational tools and interventions is critical. Tomorrow’s educational leaders will require strong AI literacy and related skills to ensure that systems that are deployed maximise the benefits to learners, educational institutions, and society.
The interdisciplinary field of Learning Analytics has started to explore how controlled and open AI applications can benefit education and learning; often involving multimodal sources of learner data. The practical significance of developing an interdisciplinary perspective at different levels of stakeholders is corroborated by recent findings on large scale implementations of analytics in education. It is clear that the implementation of technical, behavioural, economic, and pedagogical insights into educational interventions are critical to rigorous scientific evaluation. Emerging results indicate that developing actionable interventions that scale (even with rich individual learner and learning design data), is complex, and requires substantial technological, pedagogical, and organisational expertise, and training. In addition, such policies also needs to strike a balance between student privacy and what is in the best academic interests of learners and/or institutions; adding another significant layer of complexity to the effective implementation of Learning Analytics.
Many stakeholders are thus involved in -or affected by- AI and Learning Analytics, but often without being aware of it, making sustainable scaled implementation of AI and resulting learning analytics interventions in practice a challenging endeavour at best. These stakeholders include educational managers, educational designers, educational policy makers both at the organisational and regional level, student associations, employment agencies, ethics boards, data governance centres, technologists, and so forth. There is a need to involve this wider stakeholder group in this discussion, as they have urgent and substantial claims in this emerging field.
The conference facilitates discussion on these timely topics and covers various LA applications aiming to visualise learning activities, access learning behaviour, predict student performance, individualize learning, evaluate social learning and improve learning materials and tools. The conference is structured around the following three content blocks:
1. Academic research: comprehensive evaluations of recent innovations in learning and student analytics:
- Theory (e.g. advances in theoretical understanding of learning and skill development)
- Data (e.g. innovations to operationalize, quantify and observe mechanisms of learning)
- Method (e.g. developments in approaches to evaluate the impact of AI and LA on learning)
2. Policy debates: striking a balance between student privacy and data-driven quality improvements.
3. Practitioner sessions:
- LA implementation (e.g. GDPR and privacy, informed consent)
- LA in education (e.g. multimodal data, moving beyond achievement data)
- LA in the job market (e.g. informal learning recommendations, skill-based matching)
Registration
Registration is possible from 15 May, 2018. The full registration costs for the 2-day LSAC conference will be 120 euro. This includes the conference dinner, lunches and refreshments during the meeting. For PhD-students, a reduced fee of 80 euro applies.
Submission Guidelines
The organisers welcome extended abstracts (max 750 words) for the academic research parallel sessions and for the applied sessions. The practitioner’s sessions focus on practical problems, solutions and innovations related to the aforementioned categories. The academic submissions should be state-of-the-art learning and student analytics research. All submissions should follow this template: https://docs.google.com/document/d/1zfz7CAgusC_SznuOvtVklNHwZjtGP-jGLMKpD5PngbU/edit
All abstracts will go through a peer-review process.
- Submission deadline main conference: July 1st, 2018
- Submission deadline hackathon: September 1st, 2018
- Submission link: https://easychair.org/conferences/?conf=lsac2018
- Notification of acceptance to main conference: 1 August 2018
- Registration starts: May 15th, 2018
- Conference: October 22-23, 2018
- Hackathon: October 24-25, 2018
- Conference website: lsac2018.org
Organising and Programme Committee
Dr. Gábor Kismihók
TIB Hannover
Alan Berg
Dr. Stefan T. Mol
University of Amsterdam
Dr. Ilja Cornelisz
Dr. Chris van Klaveren
Vrije Universiteit Amsterdam – Amsterdam Center for Learning Analytics
Prof. Dr. Anwar Osseyran
SURF
Contact
All questions about submissions should be emailed to LSAC.FGB@vu.nl