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Objec&ves q Objec&ve #1: Provide a snapshot summary of five different NSF grants targe&ng faculty development to improve STEM educa&on q Objec&ve #2: Create an opportunity for par&cipant sharing of work and/or concerns regarding faculty development to improve STEM outcomes q Objec&ve #3: Synthesize strategies used across NSF grants to uncover shared prac&ces, findings, and implica&ons for future research Pamela L Eddy, College of William & Mary q Project Goals—high-‐impact, evidence-‐based PD and co-‐curricular prac&ces to q Improve student success q Broadened par&cipa&on q Support geoscience career pathways q PD modali;es q Face-‐to-‐face—Cohort 1 (4-‐year par&cipa&on) q Virtual—Cohort 2 (2-‐year par&cipa&on DUE 1525593, 1524605, 1524623, and 1524800 h[ps://serc.carleton.edu/sage2yc/index.html How Curriculum Work Redefines Technical Faculty Roles in the Community College Debra Bragg Community College Research Ini&a&ves University of Washington Sea[le Center for Advanced Automo&ve Technology • $4.8M -‐ NSF Advanced Technological Educa&on (ATE) Regional Center (September 2010 – present) • Macomb Community College in partnership with Wayne State University • Approach: – Offer seed funding to create, adapt, and reform curriculum – Establish 2+2+2 educa;onal pathways – Share resources via website – Integrate STEM concepts into K-‐12 curricula – Create academic and industry partnerships – Prepare students for advanced automo&ve technology careers Lessons on Faculty Development • “Faculty” – broadly defined • Faculty development through: – Curriculum development work – Teaching, guiding, and suppor&ng other faculty – Student engagement and experimenta&on (e.g., curriculum pilots) – Adapta&on to other sehngs/levels – Networking and outreach Learning Data Analytics: Providing Actionable Insights to Increase College Student Success (NSF #1444789) Jaime Lester, Higher Education (Co-PI); Huzefa Rangwala, Computer Science (Co-PI); Aditya Johri, Information Science & Technology; Carrie Klein, Higher Education George Mason University Grant Overview Project Objec;ves: Develop new computa&onal methods to analyze large and diverse types of educa&on and learning-‐related data to improve undergraduate educa&on by addressing three cri&cal issues: • discovering successful academic pathways for students; • improving pedagogy for instructors; and, • enhancing student reten&on and persistence for ins&tu&ons Central Thesis: Mining this collec&on of data will provide ac&onable insights that will make a difference for all stakeholders Our Approach: Qualita&ve case study at a large public research ins&tu&on in the Mid-‐Atlan&c region of the U.S • Focus group interviews and observa&ons with 35 faculty and advisors • Focus group interviews with 87 undergraduate students • Produced one monograph (published) and four ar&cles (one in press, three under review) focused on incen&ves and barriers to use of analy&cs data and dashboards Produced one related edited book (in press) Learning Data Analytics: Providing Actionable Insights to Increase College Student Success Findings: Incentives & Barriers to Faculty, Advisor, & Student Use of Analytics Data & Dashboards Icons licensed and used under CC 2.0 Designs altered from original A[ributed to Andoloussi, H., Hehex, D., Sargin, B., Teleymon, Wildmoser, G., via The Noun Project Small Group Ac&vity q Pick a group: – Curriculum and Instruc&on Strategies – Faculty as Adult Learners – Using Data to Improve Prac&ce q See handout for guiding ques&ons #AERA2018NSF Repor&ng Out q What ins&tu&onal changes best support faculty development to improve STEM educa&on? q How might ins;tu;onal type influence the ways in which change occurs? q What are the implica&ons for scholarship moving forward? Summary q Commonali;es across projects suppor&ng faculty development q Evidence-‐based teaching strategies q Border-‐crossing for partnerships q Ins&tu&onal type ma[ers q Real partnerships create change q Rela&onship building and social networks q Understanding change models Thank you!