Academic Workload Project

During AY 2003-04, E-CUE examined the issue of undergraduate engineering academic workload and learning. In particular, members were particularly interested in how students use their out-of-class academic work time.

FULL ECUE REPORT (ppt)

Report Summary

• QUESTIONS/ ISSUES: The following questions and issues shaped the E-CUE study:
• Is there a measurable workload problem?
• How does perception of workload connect with frustrations with learning experience?
• How might we identify students’ study patterns and how they handle different learning experiences?
• What is best-practice engineering educational experience with respect to workload?
• STUDY GOAL: Examine undergraduate engineering workload with respect to learning, assessment, teaching methods, and study habits.
• DATA: Carried out focus groups and written survey of seniors in 3 engineering departments, Mechanical Engineering, Chemical Engineering, and Electrical Engineering and Computer Science. Survey included Biggs Study Process Inventory in order to identify student study patterns.
• FINDINGS:

Measuring out-of-class academic workload

Is there a measurable workload problem? The suggested number of outside of class academic workload hours for an average number of academic subjects taken by a student (45 units) is 30 hours. In the 3 departments studied (Mechanical Engineering- Mech Eng, Chemical Engineering- Chem Eng, Electrical Engineering and Computer Science- EECS), students report average work hours as follows:

• Juniors and seniors in Chemical Engineering and EECS report higher than 30 hours per week on average for their academic workload outside of class.
• Women students in all departments average longer average hours outside of class than men students.

Factors that impact sense of academic workload

Even if academic workload is not measurably greater than the average of 30 hours per week outside of class, students’ sense of high workload can be exacerbated by poorly structured teaching/ learning experience an engineering subject. Perceptions of high workload can demotivate some students and impact performance and study habits. Students noted the following factors as leading to a sense of high workload are:

• clarity of subject learning goals;
• clarity and length of assignments;
• teaching methods- combining teaching of abstract theory with in-depth, practical hands-on labs and projects;
• projects and exams;
• assessment frequency;
• feedback on assignments;
• relationship with instructors.

Women students give slightly higher average rankings than men to many factors that are related to sense high workload.

Best-practice in academic workload and engineering learning

Best-practice teaching/ learning experiences that permit diverse student groups to handle academic workload and learn in an engineering subject were identified in Mech Eng and EECS departments. Best-practice experiences highlight use of key teaching/learning factors in subject design. The subjects include:

• 2.005- 2.006 subject series in Thermal Fluids I and II in Mech Eng department, a combined theory/ lab subject
• 6.004 Computation Structures subject in EECS, a combined theory/ lab subject

Study habits, perceived workload, and learning

Students completed Biggs Study Process Inventory (SPI). Results show that students can be grouped into 4 categories of learners: deep, surface, strategic deep and strategic surface.

• Deep learners use methods to investigate subject material out of interest and study material longer than is needed for subject performance. Surface learners use methods that investigate subject material only to level needed to maximize performance in subject. Strategic learners use mix of deep and surface learning methods, however, individually strategic students tend to use lean toward deep or surface.
• Number of surface learners found in study were small.
• Strategic surface learners average slightly fewer out of class hours than deep or strategic deep learners. They also give slightly higher rankings to factors that lead to sense of high workload than deep or strategic deep learners.

Recommendations

• Continue examination of how to meet needs of diverse groups of student learners in engineering classroom.
• Create teaching/ learning guide and website that permits faculty to easily access information on designing a subject that balances key teaching/ learning factors with workload.
• Supplement website with short, hands on seminar in which instructors work on own subjects. Leave with clear direction on how to improve subjects.
• Use Biggs study process instrument to periodically check on MIT student study habits.