Research Opportunities

Looking Glass Ventures, LLC - Postdoc Researcher - Educational Technology

SBIR Award Title

SBIR Phase II: An End User Authoring Tool for Open and Intelligent Technology-Enhanced Assessments

SBIR Award Abstract

This SBIR Phase II effort will create transformative open tools to enable affordable access at scale to high quality assessments (problems & questions) for foundational subjects in secondary and post-secondary education. The explosion of online student audiences, rapid growth of Open Educational Resources (OER), and the need to support individual learners are creating an unprecedented demand for digital assessments. Assessment authoring tools today are controlled by large organizations, require advanced skills and proprie... more

Research Opportunity

Postdoc Researcher - Educational Technology
1
Yes

Address

228 Hamilton Avenue
Palo Alto
CA
94301

Officer

Shivram Venkatasubramaniam
shivramv@gmail.com
(650)380-3627

Principal Investigator

Shivram Venkatasubramaniam
shivramv@gmail.com
(650)380-3627

Description

Edfinity is a next generation platform for self-publishing and delivery of technology-enhancement assessments (“TEAs”) for K-12 and Collegiate STEM subjects.

This Small Business Innovation Research Phase II project will explore and advance the state-of-the-art in Human Computer Interaction. This NSF SBIR Phase II effort will explore the implementation of a cloud-based, collaborative authoring tool to achieve an order of magnitude reduction in technical skills required to author TEAs and distribute them as embeddable widgets on disparate assessment platforms. Thus, it will reduce the chasm between end user educators and professional TEA authors. Additionally, it will advance the frontiers of TEA authoring beyond individual assessments to encompass the creation of personalized TEA pathways for diverse learners. The project will advance the state-of-the-art in Human Computer Interaction, and explore novel technologies including (a) visual abstraction and symbolic representation of programming constructs associated with complex TEA authoring into a modern, intuitive user interface, and (b) implementation of a TEA representation that imparts 'platform agnostic' behavioral intelligence to TEAs, making them usable in disparate assessment delivery platforms.
Training and learning opportunities include (a) an immersive experience in an intellectually challenging product development environment, (b) continuous interaction with a team of accomplished entrepreneurs, technologists, researchers and educators, and (c) the opportunity to develop a transformative product for some of the world’s fastest growing consumer segments.
Principal Research Areas: Human Computer Interaction, Assessment-driven Learning, Adaptive Learning, Learning Progressions, Educator Communities of Practice, Learning Analytics, Machine Learning
Skills: Software Engineering and Development, Data Sciences, UX design, UI design, Analytics, Social Media.

Proposed Interactions and Mentoring Schedule: The selected candidate will be an integral part of the product management and development teams which have an established reporting structure and communication protocol. In addition to being an integral member of the team, the selected candidate will have weekly meetings with an assigned mentor. The mentor will aid and guide the candidate on execution of assigned responsibilities, and presenting work products to the team. The candidate will also be provided opportunities to present research in various corporate, academic and professional settings.

Location(s): Cincinnati, Boston or Palo Alto.

Desired Knowledge

The ideal candidate would have a doctoral degree in one of the following disciplines – Mathematics, Statistics, Computer Science, Cognitive Science, Data Sciences or Engineering, with a strong grounding in both qualitative and quantitative research. Additionally, we are looking for moderate to strong skills in one or more of the following - programming using python and/or rails, development of web or mobile apps, user experience or user interface design, machine learning, statistical data analysis, measurement and interpretation of usage analytics. Keen interest in education and educational technology would be a plus, as would some teaching experience at the K-12 or collegiate levels in any STEM subject.

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