MS Thesis Guidelines & Checklist
The post-secondary education
of many students culminates in the MS thesis. In the ECE department
the thesis committee consists of two members of the ECE department
and a graduate representative assigned by the university. The
committee must approve both an oral defense of the student's
thesis work and the written thesis. Unfortunately, standards
and expectations for thesis quality and scope vary among faculty.
To maintain a greater degree of consistency, here is a checklist
of criteria that I will rely on to determine whether an MS thesis
is of acceptable quality or not. This is designed for a thesis
that proposes something new, such as an algorithm or design,
to solve a specific problem. It may not apply to theses that
make theoretical advances.
Introduction (First Chapter)
- Problem: Is the problem clearly stated and fully
- Objectives: Are the objectives of the thesis clearly
stated in the introduction chapter?
- Significance: Is the significance of the proposed solutions
- Literature Summary: Does the thesis summarize solutions proposed
by others that have been published in conference proceedings
and journal articles? If no solutions have been proposed, has
a summary of the most closely related literature been summarized
and it's relationship to the problem of interest fully explained?
- Current Practice: Does the thesis summarize the "best
current practice", which is how people presently solve the
problem in practice.
- What's Better?: Does the thesis explain the potential
advantages of the new design as compared to other proposed solutions
in the literature and the best current practice?
- Contributions: Does the first chapter clearly and concisely
summarize the contributions of the thesis?
- Mastery of Knowledge: Does the thesis make it clear that the
student has mastered the methodology necessary to solve the problem?
For a thesis proposing new algorithms, this may be a demonstrated
mastery of the knowledge of statistical estimation, signal processing,
image processing, pattern recognition, nonlinear optimization,
- Constraints: Are the design constraints and/or specifications
clearly and quantitatively specified? Is relevant domain knowledge
appropriately considered and leveraged to improve the design?
- Tradeoffs and Metrics: Are design tradeoffs recognized and discussed?
In many cases this may be the dollar cost of design features
or the computational cost of algorithm components. Are quantitative
metrics appropriately defined to quantify the design tradeoffs?
- Design Rationale: Are design decisions appropriately justified
based on the application and/or sound design principles, or is
the design merely empirical?
- Optimality*: Are any optimality claims made? Is "optimal"
defined? Are the claims justified?
- Benchmark*: Did the student choose an appropriate
standard of comparison?
- Performance Metrics: Are the performance metrics appropriate?
Is the choice of a performance metric sufficiently justified?
- Sufficiency: Once the assessment is completed, will
it clearly demonstrate whether the proposed solution is better
and/or meets the stated specifications?
- Prospective Assessment: Was the same data used to motivate and
refine the design as was used to measure performance of the new
technique? New data should be used. If it wasn't, the use of
the same data for both development and validation must be justified
and the potential bias in the results must be fully discusssed.
- Experimental Design: If new data was collected, was a testable
hypothesis stated before it was collected? Was the methodology
for testing the hypothesis fully developed before the new data
- Presentation: Are the results appropriately presented
with tables and figures?
- Captions: Do the figure and table captions sufficiently
summarize the content of the figures and tables? Can the figures
and tables be understood from the caption alone? Are the axes
clearly defined? Are units provided for all axes and table entries?
- Sufficient?: Are the results sufficient to judge the
performance of the proposed solution?
- Better?: Do the results clearly indicate the improvement
of performance of the proposed solution as compared to a reasonable
standard of comparison?
- Anomalies: Does the discussion explain any discrepancies
or anamolies in the results?
- Weaknesses: Does the discussion discuss pitfalls
and weaknesses in the proposed solution? Is the solution always
better, or only under certain conditions? If the latter, what
are the conditions?
- Interpretation: Is the interpretation of the results
accurate and reasonable? Or are the claims broader than what
is supported by the results?
- Contributions: Does the conclusion concisely summarize
the contributions of the thesis (again)?
- Futher Research*: Does the conclusion discuss ideas for
future research and further improvements in the proposed solution?
- Conclusion: Does the conclusion concisely state what
can be concluded from this work?
- Grammar: Is the grammar and prose of sufficient
quality for an MS thesis?
- Organization: Is the thesis appropriately organized?
Are the section headings appropriate and clear?
* These categories may not apply to all theses.