LearnLab 2018 - Simon Initiative's LearnLab Summer School
Date2018-07-27 - 2018-08-03
Deadline2018-05-11
VenueCarnegie Mellon University, USA - United States
Keywords
Topics/Call fo Papers
We invite applications for participation in an intensive 1-week summer school on advanced learning technologies and technology-enhanced learning experiments. The summer school will provide a conceptual background and considerable hands-on experience in developing, running and analyzing technology-enhanced learning experiments. Materials are drawn from research as well as abbreviated portions from our Masters of Educational Technology and Applied Learning Science (METALS) curriculum (http://metals.hcii.cmu.edu).
Tracks
The summer school is organized into four parallel tracks: Building online courses with OLI – OLI Track (OLI), Intelligent Tutor Systems development (ITS), Computer Supported Collaborative Learning (CSCL), and Educational Data Mining (EDM). The tracks will overlap somewhat but will differ significantly with respect to the hands-on activities, which make up about half the summer school. The goal for each track is described below.
The summer school involves intensive mentoring by LearnLab researchers. The mentoring starts by e-mail before the summer school, in order to select a subject domain and task for the project, where appropriate. It continues during the summer school with a good amount of one-on-one time during the hands-on sessions. The mentors are assigned based on your interests as stated in the application. All participants will have the opportunity to interact with all course instructors, but will interact more frequently with their designated mentor.
Building online courses with OLI – OLI Track: In the OLI (Open Learning Initiative) track, you will focus on elements of effective course design including a connection between learning objectives and learning outcomes. Participants will create OLI courseware and be able to continue to use OLI tools and techniques after the summer school. Participants identify a course module that they would like to create and the expected learning outcomes. The learning outcomes will be refined making them precise and measurable. Course content, activities, and assessments to support these outcomes will be developed.
ITS track: In the intelligent tutor system development track, you will learn to implement a prototype computer-based tutor, using authoring tools developed by LearnLab researchers, such as CTAT (the Cognitive Tutor Authoring Tools) or TuTalk. CTAT supports the creation of intelligent tutoring systems. TuTalk is used to develop tutorial dialogue systems that interact with students in natural language.
EDM/track: If you are in the educational data mining track, you will learn to analyze an educational dataset using data mining tools and methods. The dataset used in hands-on activities could be one of the data sets currently in LearnLab's Data Shop or you could bring your own. This also includes qualitative datasets.
CSCL Track: If you are in the Computer Supported Collaborative Learning track, you will learn to implement automatic support for collaborative learning that could be integrated with an existing environment, such as the Virtual Math Teams online learning environment.
Format
The summer school will last five days. Each day includes lectures, discussion sessions, and laboratory sessions where the participants will work on developing a small prototype system or a small prototype experiment in an area of math, science, or language learning. The participants will use state-of-the-art tools including the Cognitive Tutor Authoring Tools and other tools for course development, environments for computer supported collaborative learning, natural language dialog, semi-automated coding of verbal data, and LearnSphere for storage of student interaction data analysis of student knowledge and performance.
On the last day, student teams will present their accomplishments to the rest of the participants. Participants are expected to do some preparation before the summer school starts.
Background Reading
For those who would like to get more information prior to submitting an application, these papers provide background about the topics, technology, and tools that will be discussed during the summer school.
Course Instructors
The primary course instructors may include:
Dr. Kenneth R. Koedinger
Human-Computer Interaction Institute
Carnegie Mellon University
Dr. Vincent Aleven
Human-Computer Interaction Institute
Carnegie Mellon University
Dr. Carolyn Penstein Rosé
Language Technologies Institute
Human-Computer Interaction Institute
Carnegie Mellon University
Mr. Norman Bier
Simon Initiative
Carnegie Mellon University
Dr. John Stamper
Human-Computer Interaction Institute
Carnegie Mellon University
Dr. Lauren Herckis
Simon Initiative/Human-Computer Interaction Institute
Carnegie Mellon University
All instructors have considerable experience in research and development in technology-based learning experiments, computer-supported collaborative learning, intelligent tutoring systems and tutorial dialogue systems. Members of the team have taught this summer school for the many years. Key instructors have also taught similar material as semester-long courses.
Required Background
The course is intended for anyone with the educational zeal who would like to learn how to create technology-enhanced learning experiments or with the appropriate computational background to actually build an intelligent tutoring system. This could include seasoned learning engineers, learning experience researchers, edtech researchers, advanced graduate students, computationally sophisticated teachers and commercial or military instructional developers. Please contact us when in doubt. In the past, people with a variety of backgrounds have attended the summer school, including those with backgrounds in psychology, education, human-computer interaction, computer science, as well as instructors working in a wide range of domains.
Applications
Please visit our online application page
Important Dates
The deadline for applications is May 11, 2018.
Admission decisions will be made by June 4, 2018.
Costs
The fee for attending the summer school is $950.00. The fee for Graduate Students is $500.00; proof of current enrollment is required for this rate. A limited number of partial scholarships for full-time graduate students are available. See the application for information about how to request a scholarship. The fee includes a continental breakfast and lunch, but not lodging or travel. Please make checks payable to Carnegie Mellon University.
Participants will be responsible for paying for their own travel, additional meals and lodging. Dorm rooms at the Carnegie Mellon University campus are available for a low rate (typically around $80/night for a single room). Rooms may be shared further reducing this cost.
Academic credit is not available, although participants will receive a certificate verifying their participation. 30 hours of Act 48 credit is available for K12 teachers.
For more information and to apply see: http://learnlab.org/index.php/simon-initiative-sum...
Tracks
The summer school is organized into four parallel tracks: Building online courses with OLI – OLI Track (OLI), Intelligent Tutor Systems development (ITS), Computer Supported Collaborative Learning (CSCL), and Educational Data Mining (EDM). The tracks will overlap somewhat but will differ significantly with respect to the hands-on activities, which make up about half the summer school. The goal for each track is described below.
The summer school involves intensive mentoring by LearnLab researchers. The mentoring starts by e-mail before the summer school, in order to select a subject domain and task for the project, where appropriate. It continues during the summer school with a good amount of one-on-one time during the hands-on sessions. The mentors are assigned based on your interests as stated in the application. All participants will have the opportunity to interact with all course instructors, but will interact more frequently with their designated mentor.
Building online courses with OLI – OLI Track: In the OLI (Open Learning Initiative) track, you will focus on elements of effective course design including a connection between learning objectives and learning outcomes. Participants will create OLI courseware and be able to continue to use OLI tools and techniques after the summer school. Participants identify a course module that they would like to create and the expected learning outcomes. The learning outcomes will be refined making them precise and measurable. Course content, activities, and assessments to support these outcomes will be developed.
ITS track: In the intelligent tutor system development track, you will learn to implement a prototype computer-based tutor, using authoring tools developed by LearnLab researchers, such as CTAT (the Cognitive Tutor Authoring Tools) or TuTalk. CTAT supports the creation of intelligent tutoring systems. TuTalk is used to develop tutorial dialogue systems that interact with students in natural language.
EDM/track: If you are in the educational data mining track, you will learn to analyze an educational dataset using data mining tools and methods. The dataset used in hands-on activities could be one of the data sets currently in LearnLab's Data Shop or you could bring your own. This also includes qualitative datasets.
CSCL Track: If you are in the Computer Supported Collaborative Learning track, you will learn to implement automatic support for collaborative learning that could be integrated with an existing environment, such as the Virtual Math Teams online learning environment.
Format
The summer school will last five days. Each day includes lectures, discussion sessions, and laboratory sessions where the participants will work on developing a small prototype system or a small prototype experiment in an area of math, science, or language learning. The participants will use state-of-the-art tools including the Cognitive Tutor Authoring Tools and other tools for course development, environments for computer supported collaborative learning, natural language dialog, semi-automated coding of verbal data, and LearnSphere for storage of student interaction data analysis of student knowledge and performance.
On the last day, student teams will present their accomplishments to the rest of the participants. Participants are expected to do some preparation before the summer school starts.
Background Reading
For those who would like to get more information prior to submitting an application, these papers provide background about the topics, technology, and tools that will be discussed during the summer school.
Course Instructors
The primary course instructors may include:
Dr. Kenneth R. Koedinger
Human-Computer Interaction Institute
Carnegie Mellon University
Dr. Vincent Aleven
Human-Computer Interaction Institute
Carnegie Mellon University
Dr. Carolyn Penstein Rosé
Language Technologies Institute
Human-Computer Interaction Institute
Carnegie Mellon University
Mr. Norman Bier
Simon Initiative
Carnegie Mellon University
Dr. John Stamper
Human-Computer Interaction Institute
Carnegie Mellon University
Dr. Lauren Herckis
Simon Initiative/Human-Computer Interaction Institute
Carnegie Mellon University
All instructors have considerable experience in research and development in technology-based learning experiments, computer-supported collaborative learning, intelligent tutoring systems and tutorial dialogue systems. Members of the team have taught this summer school for the many years. Key instructors have also taught similar material as semester-long courses.
Required Background
The course is intended for anyone with the educational zeal who would like to learn how to create technology-enhanced learning experiments or with the appropriate computational background to actually build an intelligent tutoring system. This could include seasoned learning engineers, learning experience researchers, edtech researchers, advanced graduate students, computationally sophisticated teachers and commercial or military instructional developers. Please contact us when in doubt. In the past, people with a variety of backgrounds have attended the summer school, including those with backgrounds in psychology, education, human-computer interaction, computer science, as well as instructors working in a wide range of domains.
Applications
Please visit our online application page
Important Dates
The deadline for applications is May 11, 2018.
Admission decisions will be made by June 4, 2018.
Costs
The fee for attending the summer school is $950.00. The fee for Graduate Students is $500.00; proof of current enrollment is required for this rate. A limited number of partial scholarships for full-time graduate students are available. See the application for information about how to request a scholarship. The fee includes a continental breakfast and lunch, but not lodging or travel. Please make checks payable to Carnegie Mellon University.
Participants will be responsible for paying for their own travel, additional meals and lodging. Dorm rooms at the Carnegie Mellon University campus are available for a low rate (typically around $80/night for a single room). Rooms may be shared further reducing this cost.
Academic credit is not available, although participants will receive a certificate verifying their participation. 30 hours of Act 48 credit is available for K12 teachers.
For more information and to apply see: http://learnlab.org/index.php/simon-initiative-sum...
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Last modified: 2018-04-19 09:11:21