Using a computer scoring system to correlate stress response and indicators in the Draw-a-Person-in-the-Rain Test

We designed a computer scoring system to examine the correlation between the Draw-a-Person-in-the-Rain (DAPR) Test stress indicators and the Stress Reaction Questionnaire. Participants were 155 undergraduate college students in China. We extracted and calculated the following stress indicators as depicted in the DAPR artworks: number of raindrops, average distance between raindrops, average raindrop length, and area covered by raindrops. Results demonstrate that the level of stress response had significant positive correlations with the number of raindrops, the average distance between raindrops, and the area covered by raindrops. There was no significant correlation between stress response and the average raindrop length. Satisfactory positive correlations between the DAPR stress indicators and stress response indicate that the software scoring system of DAPR is objective and accurate. The use of software in assessing DAPR artworks may solve the problem of interrater reliability and may improve the scientificity of this technique.

Promoting Effects of Computer Scoring on English Learning of College Students

In the age of economic globalization, it is important for college students to master such an international language as English. The computer scoring is an effective tool to enhance their ability of English learning. Drawing on theories of formative assessment and structural learning, this paper mainly verifies the promoting effect of computer scoring on English learning among college students. The data were collected through a questionnaire survey, and a case study was carried out on a scoring website for English writing. The results show that: formative assessment and structural learning lay the theoretical basis for computer scoring; college students generally recognize that computer scoring system greatly enhances their ability and enthusiasm of English learning; the target computer scoring system (www.pigai.org) facilitates autonomous learning under teacher supervision, with the functions on student and teacher interfaces. The research findings greatly promote the development of computer scoring and English learning among college students.

Characterizing Students’ Ideas about the Effects of a Mutation in a Noncoding Region of DNA

Understanding student ideas in large-enrollment biology courses can be challenging, because easy-to-administer multiple-choice questions frequently do not fully capture the diversity of student ideas. As part of the Automated Analysis of Constructed Responses (AACR) project, we designed a question prompting students to describe the possible effects of a mutation in a noncoding region of DNA. We characterized answers from 1127 students enrolled in eight different large-enrollment introductory biology courses at three different institutions over five semesters and generated an analytic scoring system containing three categories of correct ideas and five categories of incorrect ideas. We iteratively developed a computer model for scoring student answers and tested the model before and after implementing an instructional activity designed to help a new set of students explore this concept. After completing a targeted activity and re-answering the question, students showed improvement from preassessment, with 64% of students in incorrect and 67% of students in partially incorrect (mixed) categories shifting to correct ideas only. This question, computer-scoring model, and instructional activity can now be reliably used by other instructors to better understand and characterize student ideas on the effects of mutations outside a gene-coding region.

A Kaleidoscope of Variables

The relationship between composition courses and online education is complicated, and attempting to summarize that relationship in a blanket statement may be feeble or futile. As a field, composition faces the challenge of identifying best practices in online education at the same time that it struggles to identify standardized content for its courses. Assessment challenges also plague online composition courses. While other fields might assess student work with standardized methods or computerized scoring, the work of composition requires tedious and labor-intensive assessment methods difficult to delegate to software; indeed, a recent petition illustrates significant instructor opposition to computer scoring (Haswell & Wilson, 2013). This chapter illustrates the current state of challenging conversations within composition studies as a kaleidoscope of positions in which instructors using online education position themselves.