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1. Intelligence Augmentation for Collaborative Learning

   Roschelle, Jeremy ( January 2021 , HCI International)

   null (Ed.)

   Today’s classrooms are remarkably different from those of yesteryear. In place of individual students responding to the teacher from neat rows of desks, one more typically finds students working in groups on projects, with a teacher circulating among groups. AI applications in learning have been slow to catch up, with most available technologies focusing on personalizing or adapting instruction to learners as isolated individuals. Meanwhile, an established science of Computer Supported Collaborative Learning has come to prominence, with clear implications for how collaborative learning could best be supported. In this contribution, I will consider how intelligence augmentation could evolve to support collaborative learning as well as three signature challenges of this work that could drive AI forward. In conceptualizing collaborative learning, Kirschner and Erkens (2013) provide a useful 3x3 framework in which there are three aspects of learning (cognitive, social and motivational), three levels (community, group/team, and individual) and three kinds of pedagogical supports (discourse-oriented, representation-oriented, and process-oriented). As they engage in this multiply complex space, teachers and learners are both learning to collaborate and collaborating to learn. Further, questions of equity arise as we consider who is able to participate and in which ways. Overall, this analysis helps us see the complexity of today’s classrooms and within this complexity, the opportunities for augmentation or “assistance to become important and even essential. An overarching design concept has emerged in the past 5 years in response to this complexity, the idea of intelligent augmentation for “orchestrating” classrooms (Dillenbourg, et al, 2013). As a metaphor, orchestration can suggest the need for a coordinated performance among many agents who are each playing different roles or voicing different ideas. Practically speaking, orchestration suggests that “intelligence augmentation” could help many smaller things go well, and in doing so, could enable the overall intention of the learning experience to succeed. Those smaller things could include helping the teacher stay aware of students or groups who need attention, supporting formation of groups or transitions from one activity to the next, facilitating productive social interactions in groups, suggesting learning resources that would support teamwork, and more. A recent panel of AI experts identified orchestration as an overarching concept that is an important focus for near-term research and development for intelligence augmentation (Roschelle, Lester & Fusco, 2020). Tackling this challenging area of collaborative learning could also be beneficial for advancing AI technologies overall. Building AI agents that better understand the social context of human activities has broad importance, as does designing AI agents that can appropriately interact within teamwork. Collaborative learning has trajectory over time, and designing AI systems that support teams not just with a short term recommendation or suggestion but in long-term developmental processes is important. Further, classrooms that are engaged in collaborative learning could become very interesting hybrid environments, with multiple human and AI agents present at once and addressing dual outcome goals of learning to collaborate and collaborating to learn; addressing a hybrid environment like this could lead to developing AI systems that more robustly help many types of realistic human activity. In conclusion, the opportunity to make a societal impact by attending to collaborative learning, the availability of growing science of computer-supported collaborative learning and the need to push new boundaries in AI together suggest collaborative learning as a challenge worth tackling in coming years. 

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2. STEM Scholars Engaging in Local Problems

   Tian, E. ; Kishbaugh, T. ; Showalter, D. ; Barge, S. ( July 2022 , ASEE Annual Conference proceedings)

   Eastern Mennonite University received a 5-year S-STEM award for their STEM Scholars Engaging in Local Problems (SSELP) program. The goal of this place-based, interdisciplinary scholarship program is to increase the number of academically talented, low-income students who graduate in STEM fields and either pursue immediate employment in STEM careers or STEM-related service or continue their STEM education in graduate school. In 2018 and 2019, two cohorts of seven students were recruited to major in biology, chemistry, engineering, computer science, mathematics, or environmental science. A key part of recruitment involved on-campus interviews, during a February Scholarship Day, between STEM faculty and potential scholars. As the yield rate for the event is high (54-66%), the university has continued this practice, funding additional STEM scholarships. In order to retain and graduate the scholars in STEM fields, the SSELP faculty designed and carried out various projects and activities to support the students. The SSELP Scholars participated in a first-year STEM Career Practicum class, a one-credit course that connected students with regional STEM practitioners across a variety of fields. The scholars were supported by peer tutors embedded in STEM classes, and now many are tutors themselves. They participated in collaborative projects where the cohorts worked to identify and solve a problem or need in their community. The SSELP scholars were supported by both faculty and peer mentors. Each scholarship recipient was matched with a faculty mentor in addition to an academic advisor. A faculty mentor was in a related STEM field but typically not teaching the student. Each scholar was matched with a peer mentor (junior or senior) in their intended major of study. In addition, community building activities were implemented to provide a significant framework for interaction within the cohort. To evaluate the progress of the SSELP program, multiple surveys were conducted. HERI/CIRP Freshman Survey was used in the fall of 2018 for the first cohort and 2019 for the second cohort. The survey indicated an upward shift in students’ perception of science and in making collaborative effort towards positive change. Preliminary data on the Science Motivation Questionnaire showed that the SSELP scholars began their university studies with lower averages than their non-SSELP STEM peers in almost every area of science motivation. After over three years of implementation of the NSF-funded STEM Scholars Engaging in Local Problems program, the recruitment effort has grown significantly in STEM fields in the university. Within the two cohorts, the most common majors were environmental science and engineering. While 100% of Cohorts 1 and 2 students were retained into the Fall semester of the second year, two students from Cohort 1 left the program between the third and fourth semesters of their studies. While one student from Cohort 2 had a leave of absence, they have returned to continue their studies. The support system formed among the SSELP scholars and between the scholars and faculty has benefited the students in both their academic achievement as well as their personal growth. 

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3. Frameworks for Student Research Engagement on Interdisciplinary Civic-Engaged Projects

   Kweon, Byoung-Suk ; Belle, Lauren ; Fisher, Kim ; Burke, Tara ; Haghtalab, Joy ; Roy, Nirupam ; Bonsignore, Elizabeth ; Sachs, Naomi ; Roberts, Jennifer. ( January 2023 , The International Network for the Science of Team Science (INSciTS))

   Broadband infrastructure in urban parks may serve crucial functions including an amenity to boost overall park use and a bridge to propagate WiFi access into contiguous neighborhoods. This project: SCC:PG Park WiFi as a BRIDGE to Community Resilience has developed a new model —Build Resilience through the Internet and Digital Greenspace Exposure, leveraging off-the-shelf WiFi technology, novel algorithms, community assets, and local partnerships to lower greenspace WiFi costs. This interdisciplinary work leverages: computer science, information studies, landscape architecture, and public health. Collaboration methodologies and relational definitions across disciplines are still nascent —especially when paired with civic-engaged, applied research. Student researchers (UG/Grad) are excellent partners in bridging disciplinary barriers and constraints. Their capacity to assimilate multiple frameworks has produced refinements to the project’s theoretical lenses and suggested novel socio-technical methodology improvements. Further, they are excellent ambassadors to community partners and stakeholders. In BRIDGE, we tested two mechanisms to augment student research participation. In both, we leveraged a classic, curriculum-based model named the Partnership for Action Learning in Sustainability program (PALS). This campus-wide, community-engaged initiative pairs faculty and students with community partners. PALS curates economic, environmental, and social sustainability challenges and scopes projects to customize appropriate coursework that addresses identified challenges. Outcomes include: literature searches, wireframes, and design plans that target solutions to civic problems. Constraints include the short semester timeframe and curriculum-learning-outcome constraints. (1) On BRIDGE, Dr. Kweon executed a semester-based Landscape Architecture PALS 400-level-studio. 18 undergraduates conducted in-class and in-field work to assess community needs and proposed design solutions for future park-wide WiFi. Research topics included: community-park history, neighborhood demographics, case-study analysis, and land-cover characteristics. The students conducted an in-Park, community engagement session —via interactive posterboard surveys, to gain input on what park amenities might be redesigned or added to promote WiFi use. The students then produced seven re-design plans; one included a café/garden, with an eco-corridor that integrated technology with nature. (2) From the classic, curriculum-based PALS model we created a summer-intensive for our five research assistants, to stimulate interdisciplinary collaboration in their research tasks and co-analysis of project data products: experimental technical WiFi-setup, community survey results, and stakeholder needs-assessments. Students met weekly with each other and team leadership, exchanged journal articles, and attended joint research events. This model shows promise for integrating students more formally into an interdisciplinary research project. An end-of-intensive focus group highlighted, from the students’ perspective, the pro/cons of this model. Results: In contrasting the two mechanisms, our results include: Model 1 is tried-and-trued and produces standardized, reliable products. However, as work is group based, student independence is limited —to explore topics/themes of interest. Civic groups are typically thrilled with the diversity of action plans produced. Model 2 provides greater independence in student-learning outcomes, fosters interdisciplinary, “dictionary-building” that can be used by the full team, deepens methodological approaches, and allows for student stipend payments. Lessons learned: intensive time frame needed more research team support and ideally should be extended, when possible, over the full project-span. UMD-IRB#1785365-4; NSF-award: 2125526. 

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4. Engaging STEM Transformational Experiences for Early Momentum (ESTEEM)

   Yahdi, Mohammed ; Bracey, Zoe Buck ( November 2019 , National Science Foundation -  Hispanic-Serving Institutions (HSI) Program Principal Investigator (PI) Meeting, November 2019.)

   Need/Motivation (e.g., goals, gaps in knowledge) The ESTEEM implemented a STEM building capacity project through students’ early access to a sustainable and innovative STEM Stepping Stones, called Micro-Internships (MI). The goal is to reap key benefits of a full-length internship and undergraduate research experiences in an abbreviated format, including access, success, degree completion, transfer, and recruiting and retaining more Latinx and underrepresented students into the STEM workforce. The MIs are designed with the goals to provide opportunities for students at a community college and HSI, with authentic STEM research and applied learning experiences (ALE), support for appropriate STEM pathway/career, preparation and confidence to succeed in STEM and engage in summer long REUs, and with improved outcomes. The MI projects are accessible early to more students and build momentum to better overcome critical obstacles to success. The MIs are shorter, flexibly scheduled throughout the year, easily accessible, and participation in multiple MI is encouraged. ESTEEM also establishes a sustainable and collaborative model, working with partners from BSCS Science Education, for MI’s mentor, training, compliance, and building capacity, with shared values and practices to maximize the improvement of student outcomes. New Knowledge (e.g., hypothesis, research questions) Research indicates that REU/internship experiences can be particularly powerful for students from Latinx and underrepresented groups in STEM. However, those experiences are difficult to access for many HSI-community college students (85% of our students hold off-campus jobs), and lack of confidence is a barrier for a majority of our students. The gap between those who can and those who cannot is the “internship access gap.” This project is at a central California Community College (CCC) and HSI, the only affordable post-secondary option in a region serving a historically underrepresented population in STEM, including 75% Hispanic, and 87% have not completed college. MI is designed to reduce inequalities inherent in the internship paradigm by providing access to professional and research skills for those underserved students. The MI has been designed to reduce barriers by offering: shorter duration (25 contact hours); flexible timing (one week to once a week over many weeks); open access/large group; and proximal location (on-campus). MI mentors participate in week-long summer workshops and ongoing monthly community of practice with the goal of co-constructing a shared vision, engaging in conversations about pedagogy and learning, and sustaining the MI program going forward. Approach (e.g., objectives/specific aims, research methodologies, and analysis) Research Question and Methodology: We want to know: How does participation in a micro-internship affect students’ interest and confidence to pursue STEM? We used a mixed-methods design triangulating quantitative Likert-style survey data with interpretive coding of open-responses to reveal themes in students’ motivations, attitudes toward STEM, and confidence. Participants: The study sampled students enrolled either part-time or full-time at the community college. Although each MI was classified within STEM, they were open to any interested student in any major. Demographically, participants self-identified as 70% Hispanic/Latinx, 13% Mixed-Race, and 42 female. Instrument: Student surveys were developed from two previously validated instruments that examine the impact of the MI intervention on student interest in STEM careers and pursuing internships/REUs. Also, the pre- and post (every e months to assess longitudinal outcomes) -surveys included relevant open response prompts. The surveys collected students’ demographics; interest, confidence, and motivation in pursuing a career in STEM; perceived obstacles; and past experiences with internships and MIs. 171 students responded to the pre-survey at the time of submission. Outcomes (e.g., preliminary findings, accomplishments to date) Because we just finished year 1, we lack at this time longitudinal data to reveal if student confidence is maintained over time and whether or not students are more likely to (i) enroll in more internships, (ii) transfer to a four-year university, or (iii) shorten the time it takes for degree attainment. For short term outcomes, students significantly Increased their confidence to continue pursuing opportunities to develop within the STEM pipeline, including full-length internships, completing STEM degrees, and applying for jobs in STEM. For example, using a 2-tailed t-test we compared means before and after the MI experience. 15 out of 16 questions that showed improvement in scores were related to student confidence to pursue STEM or perceived enjoyment of a STEM career. Finding from the free-response questions, showed that the majority of students reported enrolling in the MI to gain knowledge and experience. After the MI, 66% of students reported having gained valuable knowledge and experience, and 35% of students spoke about gaining confidence and/or momentum to pursue STEM as a career. Broader Impacts (e.g., the participation of underrepresented minorities in STEM; development of a diverse STEM workforce, enhanced infrastructure for research and education) The ESTEEM project has the potential for a transformational impact on STEM undergraduate education’s access and success for underrepresented and Latinx community college students, as well as for STEM capacity building at Hartnell College, a CCC and HSI, for students, faculty, professionals, and processes that foster research in STEM and education. Through sharing and transfer abilities of the ESTEEM model to similar institutions, the project has the potential to change the way students are served at an early and critical stage of their higher education experience at CCC, where one in every five community college student in the nation attends a CCC, over 67% of CCC students identify themselves with ethnic backgrounds that are not White, and 40 to 50% of University of California and California State University graduates in STEM started at a CCC, thus making it a key leverage point for recruiting and retaining a more diverse STEM workforce. 

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5. Remote-Region Interior Alaska Community Survey with Two Statistical Measures: Arctic Indigenous Entrepreneurial Readiness (ER); and Remote-Region Digital Technology Needs and Skills (DT).

   https://doi.org/10.18739/A20R9M54S  

   Pasch, Timothy ; Kuhlke, Olaf ; Linton, Renee ( January 2021 , Arctic Data Center)

   Between 2018 and 2021 PIs for National Science Foundation Awards # 1758781 and 1758814 EAGER: Collaborative Research: Developing and Testing an Incubator for Digital Entrepreneurship in Remote Communities, in partnership with the Tanana Chiefs Conference, the traditional tribal consortium of the 42 villages of Interior Alaska, jointly developed and conducted large-scale digital and in-person surveys of multiple Alaskan interior communities. The survey was distributed via a combination of in-person paper surveys, digital surveys, social media links, verbal in-person interviews and telephone-based responses. Analysis of this measure using SAS demonstrated the statistically significant need for enhanced digital infrastructure and reworked digital entrepreneurial and technological education in the Tanana Chiefs Conference region. 1. Two statistical measures were created during this research: Entrepreneurial Readiness (ER) and Digital Technology needs and skills (DT), both of which showed high measures of internal consistency (.89, .81). 2. The measures revealed entrepreneurial readiness challenges and evidence of specific addressable barriers that are currently preventing (serving as hindrances) to regional digital economic activity. The survey data showed statistically significant correlation with the mixed-methodological in-person focus groups and interview research conducted by the PIs and TCC collaborators in Hughes and Huslia, AK, which further corroborated stated barriers to entrepreneurship development in the region. 3. Data generated by the survey and fieldwork is maintained by the Tanana Chiefs Conference under data sovereignty agreements. The survey and focus group data contains aggregated statistical/empirical data as well as qualitative/subjective detail that runs the risk of becoming personally identifiable especially due to (but not limited to) to concerns with exceedingly small Arctic community population sizes. 4. This metadata is being provided in order to serve as a record of the data collection and analysis conducted, and also to share some high-level findings that, while revealing no personal information, may be helpful for policymaking, regional planning and efforts towards educational curricular development and infrastructural investment. The sample demographics consist of 272 women, 79 men, and 4 with gender not indicated as a response. Barriers to Entrepreneurial Readiness were a component of the measure. Lack of education is the #1 barrier, followed closely by lack of access to childcare. Among women who participated in the survey measure, 30% with 2 or more children report lack of childcare to be a significant barrier to entrepreneurial and small business activity. For entrepreneurial readiness and digital economy, the scales perform well from a psychometric standpoint. The summary scores are roughly normally distributed. Cronbach’s alphas are greater than 0.80 for both. They are moderately correlated with each other (r = 0.48, p < .0001). Men and women do not differ significantly on either measure. Education is significantly related to the digital economy measure. The detail provided in the survey related to educational needs enabled optimized development of the Incubator for Digital Entrepreneurship in Remote Communities. Enhanced digital entrepreneurship training with clear cultural linkages to traditions and community needs, along with additional childcare opportunities are two among several specific recommendations provided to the TCC. The project PIs are working closely with the TCC administration and community members related to elements of culturally-aligned curricular development that respects data tribal sovereignty, local data management protocols, data anonymity and adherence to human subjects (IRB) protocols. While the survey data is currently embargoed and unable to be submitted publicly for reasons of anonymity, the project PIs are working with the NSF Arctic Data Center towards determining pathways for sharing personally-protected data with the larger scientific community. These approaches may consist of aggregating and digitally anonymizing sensitive data in ways that cannot be de-aggregated and that meet agency and scientific community needs (while also fully respecting and protecting participants’ rights and personal privacy). At present the data sensitivity protocols are not yet adapted to TCC requirements and the datasets will remain in their care. 

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