Full Spectrum Learning

Full-Spectrum Learning (FSL) Request for Information; RFI DARPA-SN-13-04; Responses due December 19, 2012, by 4:00 PM ET. POC: CAPT Russell Shilling, Ph.D., DARPA/DSO; E-mail: DARPA-SN-13-04@darpa.mil; URL: http://www.darpa.mil/Opportunities/Solicitations/DSO_Solicitations.aspx This Request for Information (RFI) from the Defense Advanced Research Projects Agency (DARPA) Defense Sciences Office (DSO) seeks ideas, methodologies and approaches solely for information and planning purposes. Responses to this RFI may be used to support a potential new DARPA program to enable advances in new and revolutionary approaches to training, education and learning. Intellectual, confidential, or other privileged or proprietary information contained in responses to this RFI will not be distributed outside of the Department of Defense (DoD) or US Government employees from other government agencies working with DARPA on this RFI. In the event a new DARPA program is developed in response to this RFI, and a Broad Agency Announcement is issued, no intellectual, confidential or other proprietary information received in response to this RFI will be divulged to the research community. BACKGROUND The strategies used for education and training have varied little over the past century. Although the DoD has invested in the development of simulations, games, and intelligent tutoring systems, these technological tools have been mapped directly onto traditional educational systems used in both the civilian and military sectors rather than examining the unique opportunities provided by advances in information technology to transform learning. Current systems concentrate on supplementing traditional classroom learning scenarios, and are focused on individual classes rather than curricula software platforms, including Intelligent Tutoring Systems (ITS), may make minor adaptations to determine whether a student understands a specific concept within a particular domain, but such platforms don’t fully adapt to a particular student’s measured strengths and weaknesses. They are also highly expensive and time-consuming to implement. Furthermore, current systems focus largely on traditional academic factors, with little attempt made to integrate other essential factors such as attention, affective states, and character development. DESCRIPTION DSO is seeking ideas that may be used to help frame a potential new program focused on demonstrating novel approaches, technologies, and tools that transcend singular courses and support users throughout entire curricula and ultimately all phases of life. The goal of the potential program would be to create holistic educational applications that focus on the entire student by harnessing best practices and results from neuroscience, educational research, social- emotional learning, health sciences, and creativity research. Such educational tools would adapt to individuals over time, allowing the system to understand individual strengths and weaknesses, personal preferences, attention patterns, as well as non-cognitive factors (tenacity, perseverance,  goal-setting, etc.). The system would adapt content and presentation modalities accordingly as it learns about the student. For instance, if an individual is weak in mathematics, the system would not only provide extra instruction in mathematics, but it would also take skill level into account when presenting new materials in other subject areas that require math competency. If an individual shows greater interest or responsiveness with a particular delivery format, the system would attempt to present future information using similar strategies. The system architecture would be modular, extensible and scalable (open-source, open- architecture), and the content and tools would be created by a broad community of content providers. Assessment of content and effectiveness would be crowd-sourced such that the system would continue to improve over time as new material is added by content providers and feedback is provided by both teachers and students. The system would learn optimum pedagogical approaches for teaching specific topics based on usage patterns and performance of large numbers of students. An important aspect of this program is the development and integration of tools to monitor cognitive or physiological response of users while learning. Such tools may be used for periodic assessment of individual learning styles or might be used "in the background" to continuously determine if an individual is having trouble understanding a lesson, not paying attention or even bored. The system may monitor a variety of cues to determine the user's attention and emotional states. Only sensor systems that are both low-cost and accessible on a mass-produced device would be considered. An ideal system would provide social- emotional/non-cognitive tools to build confidence in the student and improve overall resilience. Rather than using a singular strategy, the system would combine multiple media formats in combinations optimized for student preference and learning styles, including lectures, e-books, intelligent tutors, games, sequential art, and social networks. The goal is not to replace the classroom instructor, but rather provide the instructor with new integrated tools to help optimize pedagogy and to improve their ability to assess student performance. Student assessment would be embedded within the application as a seamless part of the overall instructional process, and would not rely solely (if at all) on traditional notions of formal testing. Although the aim of the program would be to create new techniques to be applied to a broad range of training and education areas (military and civilian), the initial focus of this effort would be on developing middle school to college-level competency in Science, Technology, Engineering and Mathematics (STEM) areas, with emphasis on Computer Science to test these initial concepts. Computer Science is an ideal topic since it requires competency in a variety of STEM areas, and is a topic of interest in both military and civilian training. REQUESTED INFORMATION Responses are welcome from all capable sources including, but not limited to, universities, university-affiliated research centers, not-for-profit research institutions, US government- sponsored labs, and private or public companies. Presentation of appropriate preliminary data that demonstrates the feasibility of a new idea is encouraged when available. DARPA is interested in responses that may address any of the topic areas listed below. If choosing to submit a response to more than one topic area, please submit a separate response for each. Topic Area 1 (TA-1): Educational Approach and Assessment DSO is interested in developing techniques for identifying optimum pedagogical approaches that combine multiple media for instruction (games, intelligent tutors, graphic novels, e-books, social-networks, lectures, etc.) combined with non-cognitive learning. TA-1 focuses on addressing the following areas: • Identify content needed to meet educational objectives across multiple media formats. • Identify how non-cognitive factors can be integrated and assessed as an integral part of electronic instruction. • Develop rigorous assessment methodologies for both students and the overall FSL system. • Develop rigorous and reproducible metrics for measuring cognitive and non-cognitive factors. • Develop crowd-sourcing approach to optimize content based on student performance and instructor inputs. • Specify reproducible methodology for capturing techniques used by best instructors to be adapted in information technology systems. • Explain how the proposed FSL educational approach and assessment system would be integrated into educational settings (home or classroom) in a way that would be acceptable to both instructors and students. Potential performers in this area would not CREATE educational content, but would guide content creators (TA-3) in developing applications that meet educational and research goals within the FSL framework. Topic Area 2 (TA-2): Attention and Comprehension Assessment DSO is interested in identifying technologies to assess a student’s attention, comprehension, health and stress to optimize educational performance across multiple types of instructional media. Cues of interest may include, but are not limited to, facial expressions, eye tracking, posture, text analysis, voice stress, and other cues.  DSO is also interested in technologies that may be cost effective in the near future (such as EEG and electrodermal activity (EDA)) and that can also help validate the effectiveness of the FSL concept. However, high-end and high-cost techniques such as functional magnetic resonance imaging (fMRI) and neurochemistry studies would not be evaluated. All evaluated technologies must be usable and affordable within typical classroom settings. Techniques that can be integrated into tablet or other mobile computing devices are of particular interest. Topic 3 (TA-3): Education & Training Content Development DSO is interested in developing new material and identifying existing material that could be adapted to an FSL system. Media types may include intelligent tutoring systems, lectures, e- books, graphic novel content, social-networks, or games. Of particular interest is content aimed at middle-school to college-level competency in Science, Technology, Education, and Mathematics (STEM) topics with an emphasis on Computer Science. Applications must be modular so that they can be plugged into an overarching FSL architecture, and integrated with sensing/assessment techniques. Open-source solutions are preferred. Specific data supporting the impact of prior efforts in this area are strongly encouraged. We are not asking for proposed solutions. We're looking for ideas and novel approaches. Discussion of content development should include answering the following questions: • Would this approach require adapting existing material or developing new material? • What type of licensing would be required for development and use? • How is integration envisioned with both physiological and educational assessment tools as envisioned by FSL? • What technological risks would need to be addressed for integrating your approach in an FSL system? Topic Area 4 (TA-4): Open Architecture Development DSO is interested in developing overarching software based on open architecture, which would assure that content delivery, interactive assessment, and system adaptivity would be integrated into a coherent and scalable system that is compatible with use in both military and civilian education and training settings. If an FSL program were conducted, at the end of it, the architecture would be openly released for continued basic and applied research and development efforts. Design requirement would be for an open-source, open-architecture system that integrates content, assessment, and physiological monitoring within a crowd-sourced framework that can be readily adapted to other subject matter. Modularity, extensibility and scalability would be key features of system design and architecture. Topic Area 5 (TA-5): Other Innovative Approaches DSO is interested in white papers describing alternative approaches to those described in topic areas above. Solutions that emphasize scalability, extensibility, simplicity, and affordability together with metrics and assessment techniques are of particular interest. Those submitting to this topic area may also consider broader educational or training content (not just STEM / computer related) that are of relevance to children, young adults, and life-long learning in both the civilian and military populations. SUBMISSION Respondents to this RFI are encouraged to be as succinct and concise as possible, while also providing actionable insight. Separate responses are required for each thrust area addressed. Each separate thrust area response is limited to 5 pages. Appendices that provide preliminary results, publications, and other credentials will be allowed. Submissions should include: 1. PDF file in the following format: a. Cover Page (one page) i. Title ii. Organization iii. Responder’s technical and administrative points of contact (names, addresses, phone numbers, fax numbers, and email addresses) b. Abstract (12-point font, half page): Succinct technical overview of the proposed approach c. Technical Areas (12-point font, up to four pages) i. A discussion of the challenge addressed ii. A technical description of the proposed technology addressing the first three criteria listed above: 1. Novelty 2. Technical capability 3. Limitations d. Additional Information (12-point font, up to one page): i. A discussion of the remaining criteria listed above: 1. Related work and previous experience 2. Potential for civilian and/or military impact e. References to previously published work (half page) 2. Quadchart and Slides Relevant figures may be inserted into the space available on these slides. All technical and administrative correspondence, questions regarding this announcement, and how to respond to this RFI, should be sent to DARPA-SN-13-04@darpa.mil. Please refer to  “Full-Spectrum Learning/(FSL); RFI DARPA-SN-13-04” in all correspondence. Email sent directly to the Program Manager may result in delayed/no response. DISCLAIMERS AND IMPORTANT NOTES This is an RFI issued solely for information and new program planning purposes; it does not constitute a formal solicitation for proposals. In accordance with FAR 15.201(e), responses to this notice are not offers and cannot be accepted by the Government to form a binding contract. Submission is voluntary and is not required to propose to a subsequent BAA (if any) or other research solicitation (if any) on this topic. DARPA will NOT provide reimbursement for costs incurred in responding to this RFI. NO CLASSIFIED INFORMATION SHOULD BE INCLUDED IN THE RFI RESPONSE. It is the submitter's responsibility to clearly define to the Government what is considered proprietary data. Any proprietary information should be clearly labeled as “proprietary”. DARPA will disclose submission contents only for the purpose of review and evaluation. Respondents are advised that DARPA is under no obligation to acknowledge receipt of the information received or provide feedback to respondents with respect to any information submitted under this RFI.