The recently formed Learning Engineering Institute (LEI) at Arizona State University (ASU) is currently seeking Research Scientists who are conducting work related to Learning Engineering from various disciplines to join our dynamic, interdisciplinary research team. Learning Engineering is an emerging field in which evidence-based principles and methods from educational technology, learning sciences, engineering, and computer science are used to create engaging, effective learning environments and experiences that support all learners. The LEI team will engage in rigorous, scholarly research across online, hybrid, and emerging modes of teaching and learning in higher education. Key findings will inform continuous, agile improvements in ASU course design and delivery across academic departments and inform knowledge and understanding of learning across multiple contexts. LEI research scientists will work with a variety of internal and external stakeholders to improve student learning, motivation, and persistence, and increase equity and inclusion across the university. The research scientist will have the opportunity to work with a variety of extant large datasets (see learningatscale.asu.edu) as well as designing and conducting new research projects in collaboration with our LEI partners.

Ideal candidates for this position will bring strong skills in various skills and knowledge that contribute to the overarching goals of enhancing student success via learning engineering principles. Ideal candidates will have some expertise in data analytics, modeling, and data visualization; knowledge of research methodology and applications in higher education; and a passion to use big data and large-scale studies to inform improved teaching and learning that leads to student retention and success across all domains and demographic groups. LEI Research Scientist will collaborate with a variety of internal and external stakeholders on research investigations to enhance tactical and strategic decision-making, improve instruction, ensure quality courses, promote student success, and increase equity in representation and achievement for multiple populations.

ASU offers a total compensation package that includes valuable employee benefits e.g., (healthcare, financial security, retirement, family resources, tuition reduction). Click here to explore these options. Arizona State University is located in the Phoenix/Scottsdale metropolitan area and offers all of the amenities of a large urban/winter resort area.

Essential Duties

• Collaborate on research investigations to enhance tactical and strategic decision making, improve instruction, ensure quality courses, promote student success, and increase equity in representation and achievement for a wide variety of multiple populations.
• Design research studies to evaluate new and emerging technologies that have potential value for engaging effective teaching and learning.
• Design, implement, test, deploy, and maintain innovative data and education learning solutions to improve instructional operations.
• Select, develop, and/or recommend appropriate research design methodologies, data analyses, and statistical procedures.
• Coordinate and determine compatibility of data from various sources (e.g. internal ASU data tables and external datasets.
• Write and contribute to literature reviews to inform research design on a wide variety of projects.
• Seek and obtain external funding sources to support target LEI objectives.
• Communicate with internal and external constituencies to obtain necessary information
• Prepare and present research findings to a variety of academic and non-academic stakeholders
• Organize and follow through on team best practices of organizational structure for managing a high volume of research
• Ability to track, manage, and prioritize daily, weekly, and monthly tasks including research projects.
• Assumes or coordinates other duties or projects as assigned and directed.

Minimum Qualifications

PhD within a discipline that has strong potential to contribute to the process of learning engineering (e.g., learning science, data science, computer science, quantitative psychology, statistics, evaluation, human systems engineering, human factors, data analytics, UX design, instructional design), or related field by time of appointment.

Desired Qualifications

• Ideal candidates will demonstrate a strong record of scholarly writings and/or success in securing project funding.
• Strong desire to work on a team applying its collective knowledge and expertise to conduct innovative, large-scale research that informs rapid, continuous improvement in teaching and learning.
• Experience in programming, data management, descriptive and inferential statistical analysis, and modeling in R; additional experience with SQL, Python, MATLAB, or similar is desirable.
• Experience in creating data visualizations in R; ability to create dynamic visualizations using tools like Tableau or Shiny is a plus
• Experience/interest in a variety of statistical techniques; ability and interest in developing skills to match needs in these areas
• Evidence in having an interest in the unique needs of multiple learners and the technological innovations that foster their persistence and success with focus on equity and inclusion
• Evidence of effective communication and collaboration skills, especially ability to translate statistical findings for a variety of audiences
• Experience in higher education research and practice

Application deadline is December 31, 2024. Applications will continue to be accepted on a rolling basis for a reserve pool. Applications in the reserve pool may then be reviewed in the order in which they were received until the position is filled.

The positions are full-time, fiscal-year (12 months), benefits-eligible appointments with no tenure implications, and no required teaching responsibilities.

To apply, please submit the following as pdf(s) through Interfolio (1) cover letter, (2) a curriculum vitae, (3) statement of research interests, (4) two representative publications, (5) a statement addressing how your past and/or potential contributions to multiple populations and inclusion will advance ASU’s commitment to inclusive excellence, and (3) three letters of recommendation to be uploaded by your recommenders to Interfolio directly. Email and paper applications will not be accepted.

Applicants’ cover letter should include a statement addressing how their professional work and personal interests directly align with and contribute to Arizona State University’s Charter. This statement is an essential component of the application process and will be used to evaluate your suitability for the position and fit within the LEI team.

Inquiries concerning the search should be addressed to the Chair of the Search Committee: Dr. Danielle S. McNamara (dsmcnama@asu.edu). Please mention that you are applying for the Learning Engineering Institute Research Scientist position.

The College values our cultural and intellectual continually strives to foster a welcoming and inclusive environment. We are especially interested in applicants who can strengthen the academic community.

This job description provides a general guideline for the scope of the position. Additional duties and responsibilities may be assigned as needed to support the goals and mission of the Learning Engineering Institute at ASU.