The International Conference on Artificial Intelligence and Education (AIED 2013; http://aied2013.memphis.edu) and the International Conference on Educational Data Mining (EDM 2013; http://edm2013.memphis.edu) provide professional opportunity for researchers from around the world to share results of cutting-edge research from the fields of artificial intelligence (AI), data mining, computer science, cognitive and learning sciences, psychology, and educational technology that focuses on the design and effective use of advanced learning technologies. AIED researchers aim to design new technologies and advance understanding of how to use those technologies and integrate them into learning environments so that their potential is fulfilled. EDM researchers focus on working towards better use of technology for collecting, analyzing, sharing, and managing data to shed light on learning, promoting learning, and designing learning environments. Researchers from both communities aspire to better understand how people learn with technology and how technology can be used productively to help people learn, through individual use and/or through collaborations mediated by technology.
This project supports travel for advanced graduate students from US universities to attend these two conferences, held in Memphis, Tennessee, AIED 2013 from July 6 to 8, 2013, and EDM 2013 from July 10 to 12, 2013. Participating graduate students join the Doctoral Consortium (DC) tracks of the two conferences and are paired with a senior member of the AIED or EDM community for one-on-one mentoring throughout the conferences. The DC tracks of the conferences and mentor pairing are designed to provide young researchers with mentoring beyond what they get at their home institutions to help them transition from graduate school to a fruitful research career. DC track activities include structured poster sessions where students present their work, meetings with peers who have related interests, and interactions with senior members of the field. Each young researcher's one-on-one mentor will be senior members of the AIED/EDM community who shares research interests with the young researcher and who comes from a different university and has a different approach than the young researcher experiences in his/her home institution. It is expected that conversations between peers and between mentors and mentees will continue throughout each young researcher's career.
This activity supports the mission of NSF to train more advanced professionals in science, technology, engineering, and mathematics. Attending conferences is expensive for graduate students; funding their travel allows them to present their work to the larger community, speak individually with leaders in the field, and receive both support and advice from both senior researchers and peers. The AIED conference is special in its synthesis and cross-fertilization across three STEM capacities: building cutting-edge learning technologies, investigating pedagogical methods that are theoretically grounded in the cognitive, social, and learning sciences, and rigorously testing the learning environments for their effectiveness at promoting learning (in STEM and other disciplines) among K-12, college, and workplace populations. The EDM conference is special in its focus on learning how to use data collected as learners interact with learning technologies to assess learner understanding and capabilities so as to personalize feedback and advice.
This project funded doctoral students from the United States to attend the 16th International Conference on Artificial Intelligence in Education (AIED 2013: http://aied2013.memphis.edu/) and/or the co-located 6th International Conference on Educational Data Mining (EDM 2013: http://edm2013.memphis.edu) held in Memphis, Tennessee, July 6–13, 2013. The AIED and EDM conferences provide a forum for the interchange of ideas in computer science and human learning. The aim of the AIED conference is to promote the study of advanced systems in computer science applied to education, cognitive science, and human learning. The EDM conference promotes scientific research in the interdisciplinary field of educational data mining, which is concerned with developing methods for exploring the unique types of data that come from educational settings, and using those methods to better understand students and the settings which they learn in. Thus, the AIED and EDM conferences are unique in their synthesis and cross-fertilization of three STEM capacities: building cutting-edge learning technologies, investigating pedagogical methods that are theoretically grounded in the cognitive, social, and learning sciences, and rigorously testing the learning environments on learning gains, usability, and engagement. All funded students had the opportunity to attend sessions with keynote speakers, papers, posters, tutorials, and workshops as well as informally interact with peers and accomplished researchers. All students presented their own research in oral and/or poster sessions at the conference. A subset of the students participated in one of the Doctoral Consortia organized in conjunction with each conference. Thus students, presented their work to the research community, received feedback from senior researchers who served as their mentors during the conference, and were integrated into the broader AIED and EDM research communities. Many of these conversations are expected to continue during the year and many mentors are expected to serve on student dissertation committees. This professional development activity supports the mission of NSF and other granting agencies to train more advanced professionals in Science, Technology, Engineering, and Mathematics (STEM). It also directly contribute to key goals of the Cyberlearning: Transforming Education program by training graduate students to advance cutting-edge research by designing new learning technologies, understanding how people learn with technology, and increasing the affordances of technology for collection and analysis of data related to how people learn. Simply put, the AIED and EDM conferences provide foundational learning opportunities for future cyberlearning researchers. These researchers are expected to develop the next-generation cyberlearning technologies to promote STEM learning to the population at large.
