Conference Session

Work-in-Progress Posters: Computers in Education Division Poster Session

Collection

2017 ASEE Annual Conference & Exposition

Authors

Darren K. Maczka, Virginia Tech; Jacob R. Grohs, Virginia Tech

Tagged Topics

Diversity

Tagged Divisions

Computers in Education

shaping), it is especially relevant when makingdecisions regarding how to synthesize these results into practice. Any changes to assessment mustalways be accompanied with reflection about how changes might affect different people, inparticular those who have been historically disadvantaged. In short, we caution against rushing toFigure 1: Screenshot of ELAN during data analysis. The large pane contains the screen capturevideo, the smaller window shows the front facing camera of a member of the research team fordemonstration purposes. These two video streams, and the audio, are played in sync using theplayback controls below the video panes. Below that we see the audio waveform and customdefined tiers, ELAN’s term for a single analytic layer of

Conference Session

Computing Technology Session 3

Collection

2017 ASEE Annual Conference & Exposition

Authors

Swaroop Joshi, The Ohio State University; Neelam Soundarajan, Ohio State University

Tagged Topics

Diversity

Tagged Divisions

Computers in Education

public university in theMidwestern United States, participated in this study. 24 of them answered a post-activity ques-tionnaire which reflected, among other things, the demographic information. The respondentsconsisted of 83% CS majors and 17% non-majors. Three-fourths of the respondents were males.About 46% of them identified as Caucasians and an equal number were Asians, while 4% of therespondents were African-Americans and 8% Hispanics.3.2 ProceduresThe students of the course were given two assignments in the form of online-discussions on the twotools: (1) Piazza (http://piazza.com), a popular online-discussion forum used in thousandsof courses across the world, including CSE courses at this university, and (2) CONSIDER, the webapp we

Conference Session

First Year Computing Topics

Collection

2017 ASEE Annual Conference & Exposition

Authors

Vanessa Svihla, University of New Mexico; Woong Lim, University of New Mexico; Elizabeth Ellen Esterly, University of New Mexico; Irene A Lee, MIT; Melanie E Moses, Department of Computer Science, University of New Mexico; Paige Prescott, University of New Mexico; Tryphenia B. Peele-Eady Ph.D., University of New Mexico

Tagged Topics

Diversity

Tagged Divisions

Computers in Education

conductstructured observations of in-class engagement.Our preliminary analysis suggests that building on the interests, experiences, and knowledge thatpotential CS majors bring with them to class, and connecting curricula to emerging issues cansupport the learning experiences of students traditionally underrepresented in CS. For example,in the extension of the week 2 module in which students programed agents to draw their names,students were asked to create a design to reflect something about themselves. Students drewspirals, sine waves and other geometric shapes; some students wrote their names in cursive (onewith step-by-step agent instructions, another creating curves from mathematical functions); manydrew intricate emblems or logos illustrating aspects

Conference Session

First Year Computing Topics

Collection

2017 ASEE Annual Conference & Exposition

Authors

Nebojsa I Jaksic P.E., Colorado State University, Pueblo; Boyan Li; Benjamin Maestas; Katheryn Michelle Rothermal

Tagged Topics

Diversity

Tagged Divisions

Computers in Education

includes sections on previous work, curricular context, description of the robotichardware with associated integrated development environment (IDE), and educationalexperiences for the robot builders as well as the first-year students. The results of a shortquestionnaire are provided and analyzed and appropriate conclusions drawn.Previous WorkThe importance of laboratory experiences and projects in engineering education can be justifiedby various learning theories, e.g., “Kolb’s Experiential Learning Cycle.” According to Kolb1,regardless of the learning style, people learn best if they follow a cycle consisting of four steps(axes): experiencing (concrete experience), watching (reflective observation), thinking/modeling(abstract conceptualization

Conference Session

Computing Technology Session 2

Collection

2017 ASEE Annual Conference & Exposition

Authors

Petr Johanes, Stanford University; Larry Lagerstrom, Stanford University

Tagged Topics

Diversity

Tagged Divisions

Computers in Education

personalcomputer in the 1980s and the obvious possibility of using the computer as an automated form oftutor, or as an “intelligent tutoring system” (ITS). [42] An ITS is “any computer system thatperforms teaching or tutoring functions (e.g., selecting assignments, asking questions, givinghints, evaluating responses, providing feedback, prompting reflection, providing comments thatboost student interest) and adapts or personalizes those functions by modeling students’cognitive, motivational or emotional states.” [31] As might be expected, STEM topics – andcomputer science in particular – proved well-suited to these modeling efforts. Not only werecomputer scientists the ones designing the computers in the first place, but they were alsooperating in a