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We write in response to an article published in this journal by Andrew Ortony titled “Are All ‘Basic Emotions’ Emotions? A Problem for the (Basic) Emotions Construct.” The author claimed that “for all its elevated status as a basic emotion, surprise fails to satisfy the minimal requirements that [he] proposed for something to be an emotion, and if it is not an emotion, it cannot possibly be a basic emotion.” Although we acknowledge the concerns brought forth by Ortony, we respectfully disagree with his conclusion about surprise. To make a case against the assertion that surprise is valence-free, we summarize an extensive body of work showing that surprise is indeed valenced—in a specific manner (i.e., ambiguously valenced)—and that it meets all of Ortony’s criteria for an emotion. In other words, rather than being described as neither positive nor negative, this emotion is either positive or negative. We consider the data with respect to surprise as a basic emotion, and we dispute the definitions of basic emotions as “widely divergent.” Future work is needed to continue defining an emotion, and a basic emotion, but we believe this is a worthy effort toward shaping a still evolving field.

Social Network Analysis is a method to analyze individuals’ social accessibility and power. We adapt it to change inequitable issues in STEM postsecondary education. Equity issues in mathematics education, such as underrepresented women and racial disparities, are prevalent. With the social capital perspective, we investigate the demographic characteristics of influential students and their social networks. Seventeen participants are undergraduate students in an inquiry-oriented linear algebra course. The number of nominations on discussion boards as “Shout-out” is data to measure influence and map the social network. By analyzing data with UCINET, we found that (1) the most influential students are non-White males and the principal components of the network are male-dominant, and (2) there is a female-dominant small cluster and female students have reciprocal networks. This study suggests further discussions of (1) how discussion boards position students with the social capital perspective and (2) intersectionality, especially for women of color.

Social Network Analysis is a method to analyze individuals’ social accessibility and power. We adapt it to change inequitable issues in STEM postsecondary education. Equity issues in mathematics education, such as underrepresented women and racial disparities, are prevalent. With the social capital perspective, we investigate the demographic characteristics of influential students and their social networks. Seventeen participants are undergraduate students in an inquiry-oriented linear algebra course. The number of nominations on discussion boards as “Shout-out” is data to measure influence and map the social network. By analyzing data with UCINET, we found that (1) the most influential students are non-White males and the principal components of the network are male-dominant, and (2) there is a female-dominant small cluster and female students have reciprocal networks. This study suggests further discussions of (1) how discussion boards position students with the social capital perspective and (2) intersectionality, especially for women of color.

This study explores the use of a holistic virtual simulation platform to develop preservice teachers’ questioning and discussion skills. Asking effective questions and facilitating discussions are fundamental yet challenging skills for pre-service teachers to master. Robust experiences for pre-service teachers to practice questioning and discussion skills in a COVID-19 free environment are needed. Kolb’s (1984) experiential learning theory combined with Ericsson’s (2007) deliberate practice was used as a theoretical framework to design the holistic virtual simulation platform. The platform combines a synchronous experience using a virtual simulation where participants interact with avatar students, and an asynchronous experience using a learning management system for skill development. Mentor feedback based on the Danielson (2013) rubric was provided throughout both the synchronous and asynchronous events. Using a mixed-method approach, pre-service teachers’ questioning and discussion skill development and their experience of using the holistic virtual simulation platform were explored.

Social Network Analysis is a method to analyze individuals’ social accessibility and power. We adapt it to change inequitable issues in STEM postsecondary education. Equity issues in mathematics education, such as underrepresented women and racial disparities, are prevalent. With the social capital perspective, we investigate the demographic characteristics of influential students and their social networks. Seventeen participants are undergraduate students in an inquiry-oriented linear algebra course. The number of nominations on discussion boards as “Shout-out” is data to measure influence and map the social network. By analyzing data with UCINET, we found that (1) the most influential students are non-White males and the principal components of the network are male-dominant, and (2) there is a female-dominant small cluster and female students have reciprocal networks. This study suggests further discussions of (1) how discussion boards position students with the social capital perspective and (2) intersectionality, especially for women of color.

This project aims to enhance students’ learning in foundational engineering courses through oral exams based on the research conducted at the University of California San Diego. The adaptive dialogic nature of oral exams provides instructors an opportunity to better understand students’ thought processes, thus holding promise for improving both assessments of conceptual mastery and students’ learning attitudes and strategies. However, the issues of oral exam reliability, validity, and scalability have not been fully addressed. As with any assessment format, careful design is needed to maximize the benefits of oral exams to student learning and minimize the potential concerns. Compared to traditional written exams, oral exams have a unique design space, which involves a large range of parameters, including the type of oral assessment questions, grading criteria, how oral exams are administered, how questions are communicated and presented to the students, how feedback were provided, and other logistical perspectives such as weight of oral exam in overall course grade, frequency of oral assessment, etc. In order to address the scalability for high enrollment classes, key elements of the project are the involvement of the entire instructional team (instructors and teaching assistants). Thus the project will create a new training program tomore »prepare faculty and teaching assistants to administer oral exams that include considerations of issues such as bias and students with disabilities. The purpose of this study is to create a framework to integrate oral exams in core undergraduate engineering courses, complementing existing assessment strategies by (1) creating a guideline to optimize the oral exam design parameters for the best students learning outcomes; and (2) Create a new training program to prepare faculty and teaching assistants to administer oral exams. The project will implement an iterative design strategy using an evidence-based approach of evaluation. The effectiveness of the oral exams will be evaluated by tracking student improvements on conceptual questions across consecutive oral exams in a single course, as well as across other courses. Since its start in January 2021, the project is well underway. In this poster, we will present a summary of the results from year 1: (1) exploration of the oral exam design parameters, and its impact in students’ engagement and perception of oral exams towards learning; (2) the effectiveness of the newly developed instructor and teaching assistants training programs (3) The development of the evaluation instruments to gauge the project success; (4) instructors and teaching assistants experience and perceptions.« less