Austin Pack
Biographic Data
| ID | 5997704 |
|---|---|
| NAME | Austin Pack |
| GIVEN NAMES | Austin |
| FAMILY NAME | Pack |
| SIGNATURE | PACK A |
| AFFILIATIONS | Brigham Young University–Hawaii |
| ORCID | 0000-0002-3861-5620 |
| VERIFIED | Yes |
| TOTAL WORKS | 10 |
| TOTAL CITATIONS | 14 |
| WORKS AS AUTHOR | 10 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 3 |
The Effects of Artificial Intelligence-Based Dynamic Written Corrective Feedback on Second Language Writing and User Sentiment
This study investigated the efficacy of artificial intelligence-based dynamic written corrective feedback on second language writing accuracy, fluency, complexity, and functional adequacy, while also examining user sentiment for teacher and students. Utilizing Claude 3 Opus as the primary artificial intelligence tool, the research compares artificial intelligence-generated feedback to traditional teacher-provided dynamic written corrective feedba…
Exploring the influence of audience familiarity on speaker anxiety and performance in virtual reality and real-life presentation contexts
Virtual reality (VR) offers immense freedom in the design of virtual instructional environments, but little guidance exists on how to capitalise on this freedom. This article reports on a study exploring how audience familiarity influences public speaking anxiety (PSA) and performance in a presentation speaking task in virtuo and in situ. Questionnaire instruments were used to gauge the PSA, motivation, focus, and self-confidence of 10 undergradu…
Using Artificial Intelligence in Tesol
While recent and significant progress made in natural language processing and artificial intelligence (AI) has the potential to drastically influence the field of language education, many language educators and administrators remain unfamiliar with these recent technological advances and their pedagogical implications. The primary purpose of this paper is to raise the awareness of language educators regarding ethical and pedagogical issues stemmi…
AI-generated feedback on writing
The question of how generative AI tools, such as large language models and chatbots, can be leveraged ethically and effectively in education is ongoing. Given the critical role that writing plays in learning and assessment within educational institutions, it is of growing importance for educators to make thoughtful and informed decisions as to how and in what capacity generative AI tools should be leveraged to assist in the development of student…
Not quite eye to A.I.
Generative artificial intelligence (GenAI) can be used to author academic texts at a similar level to what humans are capable of, causing concern about its misuse in education. Addressing the role of GenAI in teaching and learning has become an urgent task. This study reports the results of a survey comparing educators’ (n = 68) and university students’ (n = 158) perceptions on the appropriate use of GenAI in the writing process. The survey inclu…
Technology acceptance model and multi-user virtual reality learning environments for Chinese language education
Virtual reality is a rapidly developing technology and its applications are being explored in a variety of educational fields. While an increasing amount of attention is being paid to VR as a language learning tool, there remains less research on using VR with languages other than English. Adapting the Technology Acceptance Model, this study investigated learner attitudes towards Hubs by Mozilla, a multi-user VR learning environment, for the purp…
Using Generative Artificial Intelligence for Language Education Research
Progress made in Natural Language Processing (NLP) and Artificial Intelligence (AI) in recent years has resulted in these tools becoming more accessible for individuals who lack professional training. Of particular note are large language models, such as OpenAI's GPT‐3.5. Discussions of utilizing AI for language education usually focus on the impact the technology will have on students and teachers. Less frequently the center of attention is how …
A Network Analysis of L2 Motivational Factors
Motivational factors have long attracted the attention of researchers and educators with their potential to shed light on what drives effective language learning. Although current research now views language learning motivation as a Complex Dynamic System (CDS), there is a dearth of empirical studies utilizing network analysis to understand how motivational systems operate. This exploratory study investigated the structure and connectivity of a s…
Understanding learners’ acceptance of high-immersion virtual reality systems
Towards a non‐dichotomous view of motivators and demotivators in language learning
This study explores the motivational dynamics and motivational factors of 60 first‐year English for Academic Purposes learners. Data were collected over a 10‐week period by means of motivation journals and focus group discussions. The findings indicate that students’ motivation levels changed frequently from day to day and that motivational factors can serve as both motivators and demotivators as their strength and polarity change according to in…
Using Artificial Intelligence in Tesol
While recent and significant progress made in natural language processing and artificial intelligence (AI) has the potential to drastically influence the field of language education, many language educators and administrators remain unfamiliar with these recent technological advances and their pedagogical implications. The primary purpose of this paper is to raise the awareness of language educators regarding ethical and pedagogical issues stemmi…
Using Generative Artificial Intelligence for Language Education Research
Progress made in Natural Language Processing (NLP) and Artificial Intelligence (AI) in recent years has resulted in these tools becoming more accessible for individuals who lack professional training. Of particular note are large language models, such as OpenAI's GPT‐3.5. Discussions of utilizing AI for language education usually focus on the impact the technology will have on students and teachers. Less frequently the center of attention is how …
A Network Analysis of L2 Motivational Factors
Motivational factors have long attracted the attention of researchers and educators with their potential to shed light on what drives effective language learning. Although current research now views language learning motivation as a Complex Dynamic System (CDS), there is a dearth of empirical studies utilizing network analysis to understand how motivational systems operate. This exploratory study investigated the structure and connectivity of a s…
Towards a non‐dichotomous view of motivators and demotivators in language learning
This study explores the motivational dynamics and motivational factors of 60 first‐year English for Academic Purposes learners. Data were collected over a 10‐week period by means of motivation journals and focus group discussions. The findings indicate that students’ motivation levels changed frequently from day to day and that motivational factors can serve as both motivators and demotivators as their strength and polarity change according to in…
Understanding learners’ acceptance of high-immersion virtual reality systems
Towards a non‐dichotomous view of motivators and demotivators in language learning
This study explores the motivational dynamics and motivational factors of 60 first‐year English for Academic Purposes learners. Data were collected over a 10‐week period by means of motivation journals and focus group discussions. The findings indicate that students’ motivation levels changed frequently from day to day and that motivational factors can serve as both motivators and demotivators as their strength and polarity change according to in…
AI-generated feedback on writing
The question of how generative AI tools, such as large language models and chatbots, can be leveraged ethically and effectively in education is ongoing. Given the critical role that writing plays in learning and assessment within educational institutions, it is of growing importance for educators to make thoughtful and informed decisions as to how and in what capacity generative AI tools should be leveraged to assist in the development of student…
Not quite eye to A.I.
Generative artificial intelligence (GenAI) can be used to author academic texts at a similar level to what humans are capable of, causing concern about its misuse in education. Addressing the role of GenAI in teaching and learning has become an urgent task. This study reports the results of a survey comparing educators’ (n = 68) and university students’ (n = 158) perceptions on the appropriate use of GenAI in the writing process. The survey inclu…
Technology acceptance model and multi-user virtual reality learning environments for Chinese language education
Virtual reality is a rapidly developing technology and its applications are being explored in a variety of educational fields. While an increasing amount of attention is being paid to VR as a language learning tool, there remains less research on using VR with languages other than English. Adapting the Technology Acceptance Model, this study investigated learner attitudes towards Hubs by Mozilla, a multi-user VR learning environment, for the purp…
Using Generative Artificial Intelligence for Language Education Research
Progress made in Natural Language Processing (NLP) and Artificial Intelligence (AI) in recent years has resulted in these tools becoming more accessible for individuals who lack professional training. Of particular note are large language models, such as OpenAI's GPT‐3.5. Discussions of utilizing AI for language education usually focus on the impact the technology will have on students and teachers. Less frequently the center of attention is how …
A Network Analysis of L2 Motivational Factors
Motivational factors have long attracted the attention of researchers and educators with their potential to shed light on what drives effective language learning. Although current research now views language learning motivation as a Complex Dynamic System (CDS), there is a dearth of empirical studies utilizing network analysis to understand how motivational systems operate. This exploratory study investigated the structure and connectivity of a s…
Exploring the influence of audience familiarity on speaker anxiety and performance in virtual reality and real-life presentation contexts
Virtual reality (VR) offers immense freedom in the design of virtual instructional environments, but little guidance exists on how to capitalise on this freedom. This article reports on a study exploring how audience familiarity influences public speaking anxiety (PSA) and performance in a presentation speaking task in virtuo and in situ. Questionnaire instruments were used to gauge the PSA, motivation, focus, and self-confidence of 10 undergradu…
Using Artificial Intelligence in Tesol
While recent and significant progress made in natural language processing and artificial intelligence (AI) has the potential to drastically influence the field of language education, many language educators and administrators remain unfamiliar with these recent technological advances and their pedagogical implications. The primary purpose of this paper is to raise the awareness of language educators regarding ethical and pedagogical issues stemmi…
The Effects of Artificial Intelligence-Based Dynamic Written Corrective Feedback on Second Language Writing and User Sentiment
This study investigated the efficacy of artificial intelligence-based dynamic written corrective feedback on second language writing accuracy, fluency, complexity, and functional adequacy, while also examining user sentiment for teacher and students. Utilizing Claude 3 Opus as the primary artificial intelligence tool, the research compares artificial intelligence-generated feedback to traditional teacher-provided dynamic written corrective feedba…
Psychology (8 works) · Computer Science (7 works) · Mathematics education (5 works) · Artificial Intelligence in Healthcare and Education (4 works) · Text Readability and Simplification (4 works) · Artificial Intelligence (3 works) · Human–computer interaction (3 works) · Pedagogy (3 works) · Perception (3 works) · Virtual reality (3 works)