An official website of the United States government
The 2021 return to face-to-face teaching and proctored exams revealed significant gaps in student learning during remote instruction. The challenge of supporting underperforming students is not expected to abate in the next 5-10 years as COVID-19-related learning losses compound structural inequalities in K-12 education. More recently, anecdotal evidence across courses shows declines in classroom attendance and student engagement. Lack of engagement indicates emotional barriers rather than intellectual deficiencies, and its growth coincides with the ongoing mental health epidemic. Regardless of the underlying reasons, professors are now faced with the unappealing choice of awarding failing grades to an uncomfortably large fraction of classes or awarding passing grades to students who do not seem prepared for the workforce or adult life in general. Faculty training, if it exists, addresses neither the scale of this situation nor the emotional/identity aspects of the problem. There is an urgent need for pedagogical remediation tools that can be applied without additional TA or staff resources, without training in psychiatry, and with only five or eight weeks remaining in the semester. This work presents two work-in-progress interventions for engineering faculty who face the challenges described above. In the first intervention, students can improve their exam score by submitting videos of reworked exams. The requirement of voiceover forces students to understand the thought process behind problems, even if they have copied the answers from a friend. Incorporating peer review into the assignment reduces the workload for instructor grading. This intervention has been successfully implemented in sophomore- and senior-level courses with positive feedback from both faculty and students. In the second intervention, students who fail the midterm are offered an automatic passing exam grade (typically 51%) in exchange for submitting a knowledge inventory and remediation plan. Students create a glossary of terms and concepts from the class and rank them by their level of understanding. Recent iterations of the remediation plan also include reflections on emotions and support networks. In February 2023, the project team will scale the interventions to freshman-level Introductory Programming, which has 400 students and the highest fail/withdrawal rate in the college. The large sample size will enable more robust statistics to correlate exam scores, intervention rubric items, and surveys on assignment effectiveness. Piloting interventions in a variety of environments and classes will establish best pedagogical practices that minimize instructors’ workload and decision fatigue. The ultimate goal of this project is to benefit students and faculty through well-defined and systematic interventions across the curriculum.
more »
« less
This content will become publicly available on June 1, 2026
WiP: Metacognitive and social-emotional-learning interventions in first-year Calculus
Student performance and retention in STEM majors is a major concern in higher education. Individual attention and coaching are effective at improving the retention of under-performing students, but these tools are too labor-intensive for faculty to apply in large introductory courses. Additionally, many struggling students are limited by non-cognitive factors such as fear of failure, social anxiety, and general overwhelm. There is a need for large-format, scalable instructional tools that both engage students in course material and address non-cognitive factors in an appropriate way. This Work In Progress will present the effects of a remedial intervention, the “reflective knowledge inventory”, at improving student outcomes in Calculus 1. This intervention was developed over several years in sophomore through senior-level engineering classes post-pandemic. In the intervention, students improve their exam score by submitting a “reflective knowledge inventory”. Expert learners know that new skills are best built on existing knowledge, and that big problems should be broken into smaller tasks. Novice learners are more likely to feel overwhelmed and panicked, especially when they know they are underperforming. We attempted to design a remedial assignment that scaffolds students through the process of identifying technical strengths to build on and breaking weaknesses into manageable chunks. Briefly, students create a glossary of terms and concepts from the class and rank them by their level of understanding. Importantly, the assignment also includes reflections on emotions, barriers, and support networks. This work will combine quantitative analysis of student grades with thematic analysis of student submissions to determine the effectiveness of the intervention.
more »
« less
- Award ID(s):
- 2417341
- PAR ID:
- 10636627
- Publisher / Repository:
- ASEE Conferences
- Date Published:
- Format(s):
- Medium: X
- Location:
- Montreal, Quebec, Canada
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Improving the level of success of students from low socioeconomic backgrounds in science, technology, engineering, and mathematics (STEM) disciplines has been a prevailing concern for higher education institutions for many years. To address this challenge, a pilot initiative has been implemented with engineering students at the University of Puerto Rico Mayaguez, a recognized Hispanic-serving institution. Over the past four years, the Program for Engineering Access, Retention, and LIATS Success (PEARLS) has brought in an innovative intervention model that combines elements from socio-cognitive career theories and departure studies to impact students' success. PEARLS has established a comprehensive range of tools and services, including mentorship, professional readiness training, research opportunities, scholarships, and peer mentor activities. These efforts have led to impressive outcomes, including a significant increase in retention and persistence rates, increased graduation rates having quad-fold those observed in the general student population, and an impressive record of engagements in industry, research, and leadership experiences. This paper discusses the program structure and outcomes from five perspectives that include background experiences, the structure of provided services, the results of their execution, the elements of knowledge derived from its application, and the challenges experienced throughout its implementation.more » « less
-
To enhance conceptual understanding of mathematical models for inventory management, we developed poetry-writing assignments for a required, upper-level undergraduate course in an industrial and systems engineering program. Specifically, two poetry-writing assignments were incorporated into an inventory and supply chain system design and control course. The first assignment, due one week before the first term exam, asked students to write a poem about a concept, model or topic related to deterministic inventory modeling. The second and assignment, due one week before the second term exam, asked the students to write a poem about a concept, model or topic related to stochastic inventory modeling. The students were also asked to respond to several open-ended questions on their approach to writing the poems and their assessment of the impact of these poetry writing on improving their conceptual understanding of the underlying mathematical models. Data was collected in Spring 2022 semester. The student written-poetry will be analyzed for correctness and to identify misunderstandings or gaps in understanding. In this paper, we will present our findings from the content analysis of student-written poetry and our preliminary findings on the effectiveness of poetry-writing assignments to enhance conceptual understanding of mathematical models for inventory management.more » « less
-
This study investigated the effects of a team-based modeling intervention that implemented reflective practices to support students’ self-regulated learning in the context of modeling assignments. We used a mixed method design to answer the three research questions: (1) What metacognitive strategies do students, organized in teams, implement when solving computational modeling assignments? (2) What are students’ levels of performance in solving computational modeling assignments in teams? (3) What are the relationships between teams’ level of confidence and their implemented metacognitive strategies and level of performance in the computational modeling assignment? The learning intervention was guided by a reflective modeling practitioner model, bringing together modeling practices with elements of selfregulated learning. The results illustrate students’ levels of self-reported confidence in three levels, showing that from the twelve teams studied, seven reported an increase in confidence as the project progressed, three reported a decrease in their confidence, and two reported an initial struggle, but their confidence increased as they completed the assignment. The implications relate to the learning interventions in the team modeling activity that can influence the teams’ reported selfconfidence, which can impact the skills students acquire and the strategies they use when faced with challenges.more » « less
-
Students come to learning in engineering classrooms with misconceptions about the concepts covered in engineering course contents. However, instructional efforts often do not effectively address misconceptions in students’ prior knowledge. Concept inventories (CIs) are often relied upon to identify misconceptions in students’ prior knowledge. However, many instructors never benefit much from using CIs because they lack either the know-how, time commitment, or statistical skills required to use them efficiently and effectively. Furthermore, there sometimes are ambiguities about how to interpret students’ CI scores. The Electric Circuit Concepts Diagnostic (ECCD) project team will address these limitations of CIs by creating a web-based electric circuit concept inventory that: (i.) provides an immediate and multipurpose feedback system for reporting about students’ circuits and electricity prior knowledge; (ii.) differentiates, with a high probability, between a lack of prior knowledge and misconceptions; and (iii.) uses a scheme of multidimensional knowledge profiles to report on students’ prior knowledge and misconceptions. The project will integrate the affordances of cognitive diagnostic modeling (CDM), multitier testing frameworks, and computer-assisted testing to realize these project objectives. This work-in-progress report introduces the objectives of ECCD inventory to the ECE research and teaching community.more » « less
