Contribution: Demonstrates how to use experiential learning (EL) to improve argumentative writing. Presents the design and development of a natural language processing (NLP) application for aiding instructors in providing feedback on student essays. Discusses how EL combined with automated support provides an analytical approach to improving written-communication skills. Background: High-quality, timely, feedback is an effective way to improve students’ writing. However, large class sizes and limited instructor backgrounds often make formative feedback impossible. Recent trends, including lowering entry requirements, have added to these challenges. Assistive technologies for implementing inclusive education provide viable solutions. Research Questions: 1) How and why can EL be used to develop argumentative writing skills in university STEM students? 2) How can technologies be developed to support using EL in teaching writing? and 3) How might the holistic impact of using such analytic techniques be evaluated? Methodology: Participants in an EL project were assigned two essays in sequence. They were given instructions on making good arguments and shown how to use an analytic rubric to maximize their scores. The essays were hand scored by tutors who provided scores for each dimension of the rubric. Subsequently, the content and argumentation of the essays were analyzed using NLP techniques to obtain independent scores. Qualitative data were also collected. Findings: The project produced transformative writing experiences for the participants. It showed how analytical techniques help improve writing skills and how relevant automated instructor assistance can be developed using NLP technologies.

This paper reports on a study conducted by college students at a private university in Saudi Arabia. The research examines the online learning experiences of their peers during the first wave of the coronavirus covid-19 pandemic. Many assumptions exist about online learning and its impact in higher education, but these are mainly based on the views of instructors and leaders of institutions. Hitherto, the perspectives of those meant to be beneficiaries of digital technologies have been given little consideration even though students use cyberspace for academic work and beyond. To address this silence, a group of student-researchers conducted a case study to examine students’ views of cyberlearning. The research used a qualitative analysis approach to address the following questions: (1) What were the cyberlearning experiences of students at our university during the first two semesters of lockdown? (2) What are students’ understandings of cyberlearning? (3) What are their aspirations for cyberlearning? Data were collected through an online survey administered to the entire student body at the university. Responses were received from 3574 students. The data were analysed using thematic analysis. The research participants perceive cyberlearning to be the same as online learning and see it as a viable educational option. They reported that the dominant mode of instruction in online classrooms is instructors delivering information. Respondents also highlighted the need for improved online teaching pedagogies and curbing academic dishonesty in online classrooms. Students’ aspirations for cyberlearning were clearly articulated. Respondents suggested that increasing online learning opportunities would have a positive impact on their academic progress. Through this research students demonstrate a sense of agency and provide opportunities for equity strategies at their university. The results show that serious attempts should be made to include cyberlearning as part of everyday educational activity in an attempt to increase student engagement.

Many assumptions exist about online learning and its impact on college students. Hitherto, the views of those meant to be the beneficiaries of this technology have been given little consideration despite the fact that students use cyberspace for academic work and beyond. This qualitative case-study report is based on research conducted by college students at a private university in the Eastern Province of Saudi Arabia. The aim was to examine the online learning experiences of their peers during the first wave of the coronavirus global pandemic, with a view to understand how prepared their university is for an academic genre located in cyberspace. The findings are based on the perspectives of 2,298 college students responding to a survey administered to the entire student population comprising around 9,000 individuals. They suggest that increasing opportunities for cyberlearning could have positive effects on students. Also provided is cautionary advice about the need to improve teaching pedagogies and combat academic dishonesty.

Predictors of people's responses to noise inside cars are used by car companies to identify and address potential noise problems from tests. Because significant improvements have been made in engine, powertrain, and tire/road noise, it is now important to pursue improvements in wind or aerodynamic noise. While models of loudness are commonly used to predict people's responses to stationary wind noise, some wind noises are less acceptable than is predicted by loudness metrics. Additional sound characteristics may account for this. Three listening studies were designed to examine the usefulness of including additional sound quality metrics with loudness in models used to predict acceptability for stationary wind-noise sounds. Test sounds were based on recordings made in cars in a wind tunnel. Signal modification techniques were developed to decorrelate metrics across a set of sounds and to examine how acceptability changes with strengths of particular sound characteristics. Models of acceptability for stationary wind noise are significantly improved when a metric that predicts the sharpness of a sound is included in the model with the loudness metric.