This year there is a great variety of half-day workshops and tutorials in AIED’18. All workshops will be happening on June 30th. Find out the details of each below.
MORNING workshops (10.30am – 1.30pm)Gamification of Intelligent Educational Systems
Organisers: Ashok Ranchhod, Ig Ibert Bittencourt, Seiji Isotani, Vanissa Wanick
For more visit: http://gile.nees.com.br/
Abstract: It is still very common that students become disengaged or bored during the learning process by using intelligent educational systems. On the other hand, there is a growing interest in gamification as well as its applications and implications in the field of Artificial Intelligence in Education since it provides an alternative to engage and motivate students during the process of learning. The term Gamification originated in the digital media industry, however, such a term only gained widespread acceptance after late 2010. Since then most of the research on gamification in educational systems was about conceptualization, modelling and impact of use. The goal of the Workshop is to provide participants the opportunity of: i) present and discuss the empirical studies of gamification in Intelligent Educational Systems; ii) discuss and promote innovative initiatives in educational settings with the use of gamification; and iii) motivate and solidify the research on gamification of intelligent educational systems in order to leverage the development of such systems.
Ethics in AIED: Who Cares?
Organisers: Wayne Holmes, Duygu Bektik, Denise Whitelock and Beverly Woolf
For more visit: https://aiedethics.wordpress.com/
Abstract: The field of AIED raises far-reaching ethical questions with important implications for students and educators. However, most AIED research, development and deployment has taken place in what is essentially a moral vacuum (for example, what happens if a child is subjected to a biased set of algorithms that impact negatively and incorrectly on their school progress?). Around the world, virtually no research has been undertaken, no guidelines have been provided, no policies have been developed, and no regulations have been enacted to address the specific ethical issues raised by the use of Artificial Intelligence in Education.
This workshop, ETHICS in AIED: Who Cares?, is proposed as a first step towards addressing this critical problem for the field. It will be an opportunity for researchers who are exploring ethical issues critical for AIED to share their research, to identify the key ethical issues, and to map out how to address the multiple challenges, towards establishing a basis for meaningful ethical reflection necessary for innovation in the field of AIED.
The workshop will be in three parts. It will begin with ETHICS in AIED: What’s the problem?, a round-table discussion introduced and led by Professor Beverly Woolf, one of the world’s most accomplished AIED researchers. This will be followed by Mapping the Landscape, in which up to six AIED conference participants will each give a five-minute ‘lightning’ presentation on ethics in AIED research. The workshop will conclude with Addressing the Challenges, a round-table discussion session in which we will agree on a core list of ethical questions/areas of necessary research for the field of AIED, and will set out to identify next steps.
Exploring Opportunities to Standardize Adaptive Instructional Systems (AISs)
Organisers: Robert Sottilare, Robby Robson, Avron Barr, Arthur Graesser and Xiangen Hu
For more visit: https://easychair.org/cfp/
Abstract: This goal of the proposed workshop is to explore potential opportunities to standardize components or processes within a class of technologies called adaptive instructional systems (AISs) which include Intelligent Tutoring Systems (ITSs) and other learning tools and methods used to guide/optimize instruction. AISs use human variability (e.g., performance, preferences, affect) and other learner/team attributes along with instructional conditions to develop/select appropriate learning strategies (domain-independent policies) and tactics (tutor actions). Within AISs, the relationship of the learner(s) states/traits, environmental conditions (context within a learning experience), and AIS decisions is usually described by a machine learning algorithm which is used to select an action or set of actions to optimize one or more learning outcomes: knowledge acquisition, skill development, retention, performance, and transfer of skills between the instructional environment and the work or operational environment where the skills learned during instruction will be applied.
Recently, the Learning Technologies Steering Committee (LTSC) under the auspices of the IEEE Computer Society formed a 6-month Standards Study Group to investigate the possible market need for standards across AISs. An outcome of this workshop is a larger set of informed stakeholders who understand the potential of these standards and how they might influence them. Standards can enable the streamlining and innovation of processes, decrease waste and development costs, increase the efficiency of research and development, reduce adopters’ risks and integration costs, lower barriers to entry for innovative products, improve interoperability and reuse, expand markets, and support the development of new technologies and products.
Design and Application of Collaborative, Dynamic, Personalized Experimentation
Organisers: Joseph Jay Williams, Neil Heffernan and Oleksandra Poquet
For more visit: tiny.cc/edexpt
Abstract: The proposed workshop will focus on the design and application of randomized experimental comparisons, that investigate how components of digital problems impact students’ learning and motivation. In particular, the workshop will demonstrate how randomised experiments powered by artificial intelligence enhance personalised components of widely-used online problems, such as prompts for students to reflect, hints, explanations, motivational messages, and feedback. The participants will be introduced to dynamic experiments that reweigh randomization proportional to the evidence that conditions are beneficial for future students, and will consider the pros and cons of using such more advanced statistical methods to ensure research studies lead to practical improvement.
The workshop will focus on real-world online problems for which it is possible to conduct the proposed experiments. Such problems can be found on the www.assistments.org platform for middle school math, quizzes in on-campus university courses, and can be implemented in other environments, such as in the platforms delivering Massive Open Online Courses (MOOCs). For example, workshop participants can collaboratively develop hypotheses about the benefits of asking different reflective questions while solving math problems. Experiments could investigate the effects of different self-explanation prompts on the students with different levels of knowledge, verbal fluency, and motivation.
This workshop more generally aims to identify concrete, actionable ways for researchers to more easily be involved in collecting data that can directly inform the design of authentic educational resources, while testing hypothesis in more ecologically valid contexts. The workshop introduces novel methodology from statistics and machine learning that could make it easier to bridge the gap between how researchers and practitioners use randomized experimental comparisons.
Authoring and Tutoring Methods for Diverse Task Domains: Psychomotor, Mobile, and Medical
Organisers: Jason Moss and Paula Durlach
For more visit: https://easychair.org/cfp/AIED_WKSP_Psycho1
Abstract: The purpose of this workshop is to provide the AIED Community with an exploration of key issues surrounding authoring and tutoring methods for diverse task domains (i.e., psychomotor, mobile, and medical task domains) in intelligent tutoring systems (ITSs). ITSs have been developed and used in various places including military, industry, and school (e.g., Anderson, Boyle, Corbett, & Lewis, 1990; Koedinger, Anderson, Hadley, & Mark, 1997; Ritter et al., 2013; Sottilare, 2015; Sottilare & LaViola, 2015). The advantage sought of these ITSs, such as the Generalized Intelligent Framework for Training (GIFT; Sottilare, Brawner, Goldberg, & Holden, 2013), over traditional computer-based training is proven improvements in efficacy and effectiveness of training through adaptive feedback and instruction. Currently, the development and utility of intelligent tutoring systems are mostly confined to desktop environments—limiting training to conventional instructional environments—for the purpose of training predominantly cognitive and perceptual skills and functions. Thus, there is a need for the development and use of ITSs to bridge the gap between training cognitive and perceptual skills in conventional instructional environments and the training for more diverse task domains, such as psychomotor, mobile, and medical task domains. Expanding the current state of knowledge and development in authoring and tutoring methods for diverse task domains will aid in closing the gap between conventional instructional environments and training skills in environments closer in similarity to those of the real, operational environment. In order to help address this need, the proposed workshop will facilitate an interactive panel discussion from those in the ITS community for the goal of identifying and discussing the technical needs, research questions, current state of the research, and/or challenges related to authoring and tutoring methods in ITSs specific to psychomotor, mobile, and medical task domains.
AFTERNOON workshops (2.30pm – 5.30pm)Artificial Intelligence to Promote Quality and Equity in Education
Organisers: Ronghuai Huang, Dr. Kinshuk, Yanyan Li and Ting-Wen Chang
For more visit: e.bnu.edu.cn/english/
Abstract: The United Nation’s seventeen sustainable development goals to transform the world by 2030 expressed in the United Nations Sustainable Development Goals (SDG) includes a focus on quality and equity in education to promote lifelong learning for everyone. Achieving this goal creates a requirement to resolve persistent problems, such as a lack of teachers in some places and many children not developing basic reading and math skills. The aim of SDG4 is ‘Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all (SDG4, 2018). Therefore, education must find ways of achieving this goal, responding to such challenges, taking into account multiple world views and alternative knowledge systems, as well as new frontiers in science and technology such as the advances in neurosciences and the developments in digital technology, such as AI (Preparing for the future of AI, 2016; National Artificial Intelligence R&D Strategic Plan, 2016).
The integration of technology in education is speeding up the reform of the education industry, and the innovative application of AI in education can provide the public with personalized, universal, life-long and quality educational services (Preparing for the future of AI, 2016; The Human Brain Project, 2017). The use of intelligent technology to accelerate the reform of the personnel training model, teaching methods, to build a new educational system, including intelligent learning and interactive learning. AI plays an important role in education, adaptive push and lifelong educational customization.
However, global education is still facing many difficulties and challenges, such as the unbalanced development of education, political instability, environmental degradation, natural disasters, natural resources competition, and the challenge of population structure, poverty and inequality. The arrival of the AI era, it is possible to solve these problems and challenges; however, it will also increase the gap between some under-developed areas and developed areas. Also, it brings new challenges for education, such as the role of educators/learners in the AI society, digital divide, knowledge gap, and also the economy gap between developing countries and developed countries.
Assessment and Intervention during Team Tutoring
Organisers: Anne Sinatra and Jeanine Defalco
For more visit: https://easychair.org/cfp/TeamTutoringWSAIED2018
Abstract: The proposed workshop covers the topic areas of assessment and intervention during team tutoring and collaborative learning in intelligent tutoring systems (ITSs). The development of team ITSs is a time-intensive and difficult task that includes technological, instructional and design based challenges. Recent AIED journal articles have begun discussing and identifying the challenges and steps forward in approaches to successful team tutoring (Gilbert et al., 2017; Sottilare, Burke, Salas, Sinatra, Johnston & Gilbert, 2017). The goals of this workshop include providing a forum for researchers working in these up and coming areas to discuss the progress that they have made in team or collaborative tutoring, discuss the approaches that they have taken, and the challenges that they have encountered. Further, researchers who are accepted for presentation during the workshop will have an opportunity to demonstrate their team tutoring systems if applicable. After presentations of work in three topic areas: lessons learned from team ITSs, team assessment strategies and approaches, and collaborative learning/problem solving in ITSs, there will be an open discussion to identify commonalities in the approaches. Through the open discussion, the current challenges of team tutoring and gaps in the team tutoring research will be identified. This workshop is expected to be of interest to those in academia, government, and industry who are developing tutoring experiences intended to include interaction between multiple learners. The expected outcomes of the workshop include an identification of team tutoring gaps/challenges in varying learning domains, approaches that have been successful or unsuccessful in meeting those challenges, and determining the next steps in approaches that AIED researchers can use for their own team tutor development.
PALE: Personalization Approaches in Learning Environments
Ticket name: AIED Workshop 8
For more visit: http://adenu.ia.uned.es/workshops/pale2018
Abstract: The PALE 2018 workshop is a follow-up of the seven previous editions of PALE. The focus of this workshop series is on the different and complementary perspectives in which personalization can be addressed in learning environments. From the past experience we have identified new areas of interest in this research scope to complement the previous ones. In this workshop edition we would like to share and discuss the new trends in current research on how artificial intelligence combined with data science and other disciplines can support designers and developers to improve learning in its different stages. We are especially interested in the enhanced sensitivity towards the management of big educational data coming from learners’ interactions (e.g., multimodal sensor detection of attention and affect) and technological deployment (including web, mobiles, tablets, tabletops), and how can this wide range of situations and features impact on modeling the learner interaction and context. A relevant theme is understanding the impact of individual differences to improve instructional design theories and methods as well as enhance learning experience, engagement and motivation.
IMS: Intelligent Mentoring Systems
Ticket name: AIED Workshop 9
Organisers: Vania Dimitrova, Art Graesser, Antonija Mitrovic, David Shaffer and Amali Weerasinghe
For more visit: https://imsworkshop.wordpress.com/
Abstract: Mentoring is crucial for professional development and lifelong learning. It is seen by organisations as the most cost-effective and sustainable method for developing talent, for building transferable skills, for increasing motivation and confidence, for assisting with transitions across formal and informal education, for learning across workplace contexts, and for continuous career development. Studies show that investment in virtual mentors can help companies build the skills, productivity, engagement, and loyalty of their workforces. The time is ripe for the emergence of a new breed of intelligent learning systems that provide mentor-like features. Virtual mentors would be able to facilitate self-actualisation, helping learners realise their full potential. They would require a multi-faceted learner experience modelling mechanisms to get sufficient understanding of the learner, his/her current situation, and relevance to past experiences by the same learner (or by other people). Furthermore, they would embed new pedagogic strategies for promoting reflection, self-awareness, self-regulation, and self-determination through interactive interventions (e.g. open learner models, interactive conversational agents, social spaces), as well as new knowledge models formed by establishing connections and associations.
Developing intelligent mentoring systems requires deep understanding of complex issues such as learner modeling, technological capabilities, and contextual understanding, among many others. To foster this understanding, we invite the international community of AIED researchers to contribute to and shape the discussion of this stream of research in a collaborative workshop. This third edition of a workshop series will foster scientific discussion and sharing experience among researchers and practitioners to establish the state of the art and shape future directions around four main themes associated with intelligent mentoring systems – foundations, technology, and domains and contexts.
Hands-On with GIFT: A Tutorial on the Generalized Intelligent Framework for Tutoring
Ticket name: AIED Workshop 10
Organisers: Benjamin Goldberg, Jonathan Rowe, Randall Spain, Brad Mott, James Lester, Bob Pokorny and Robert Sottilare
For more visit: https://gifttutoring.org/news/75
Abstract: In this tutorial, we will showcase the Generalized Intelligent Framework for Tutoring (GIFT). GIFT is an open-source, community-driven, service-oriented plat-form for the creation, delivery, and analysis of computer-based tutoring. The tutorial will provide participants with hands-on experience using GIFT functions that support research and implementation of personalized learning experiences. Specifically, GIFT’s adaptive course flow features will be reviewed and demonstrated, with considerable hands-on time spent developing GIFT lessons and gaining familiarity with GIFT tools and authoring workflows.