A Web-based Platform for Online Programming Education

Speaker:        Dr. Alice H. Oh
                Department of Computer Science
                KAIST, Korea

Title:          "A Web-based Platform for Online Programming Education"

Date:           Friday, 30 June 2017

Time:           1:00pm to 2:00pm

Venue:          Room 1511 (near lifts 27/28), HKUST  (All are Welcome)

Abstract:

In this talk, I present Elice, an online CS (computer science) education
platform, and two sub-systems Elivate and Eliph. Elivate is a system for
taking student learning data from Elice and inferring their progress
through an educational taxonomy tailored for programming education. Elice
captures detailed student learning activities, such as the intermediate
revisions of code as students make progress toward completing their
programming exercises. With those data, Elivate recognizes each student's
progression through an education taxonomy which organizes intermediate
stages of learning such that the taxonomy can be used to evaluate student
progress as well as to design and improve course materials and structure.
With more than 240,000 intermediate source codes generated by 1,000
students, we demonstrate the practicality of the Elice and Elivate. With
Eliph, we investigate the effectiveness of visualization of code history
on peer assessment of code. Peer assessment is found to be an effective
learning tool for programming education. While many systems are proposed
to support peer assessment in programming education, little effort has
been devoted to finding ways to improve the peer assessment by assisting
the students to under- stand the programs they are assessing. Eliph is a
web-based peer assessment system for programming education with code
history visualization. Eliph incorporates the visualization of
character-level code history, selection-based history tracking and the
integration of execution events to assist students in understanding
programs written by peers, thereby leading to more effective peer
assessment. We evaluate Eliph with an experiment in an undergraduate CS
course. We show that visualization of code history has positive effects on
promoting higher quality of peer feedback by understanding the intention
and thought process.


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Biography:

RESEARCH INTERESTS

My research interests are in machine learning and computational social
science. In particular, I study a subfield of machine learning called
topic modeling which aims to discover the hidden semantic patterns in
unannotated data. I apply topic modeling to data from online social
networks (OSN) and social media which can be used as proxies for human
social behavior.

EDUCATION
Massachusetts Institute of Technology, Ph.D., Computer Science, 2008
Carnegie Mellon University, M.S., Language and Information Technologies,
2000 Massachusetts Institute of Technology, B.S., Mathematics, 1996

EXPERIENCES
Assistant Professor, Department of Computer Science, Korea Advanced
Institute of Science and Technology, 2008-Present

Visiting Scholar, Center for Research on Computation and Society, Harvard
University, 2013-2014

Research Staff, Compaq Corporation, Cambridge, MA, USA, 2000-2001
Technical Writer, Oracle Corporation, Redwood Shores, CA, USA, 1997-1998