Avoiding Algorithm Error in Computer-Aided Text Analysis: Selecting Text Analysis Software

Wobst, Janice; Lueg, Rainer

doi:10.5465/ambpp.2022.10504abstract

Proceedings

2022

DOI: 10.5465/ambpp.2022.10504abstract

|View full text |Cite

Avoiding Algorithm Error in Computer-Aided Text Analysis: Selecting Text Analysis Software

Janice Wobst

Rainer Lueg

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2023

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Towards a Digital Assessment: Artificial Intelligence Assisted Error Analysis in ESL

Borrego

2023

Integr. J. Res. Arts Humanities

View full text Add to dashboard Cite

The study we present here aims to explore the possibilities that new Artificial Intelligence tools offer teachers to design assessments to improve the written proficiency of students of English as a Foreign Language (the participants in this study have predominantly Spanish as their L1) in a University English Language Course with CEFR B2 objective. The group we are going to monitor is, as far as the Spanish university system is concerned, on average: more than sixty students, with diverse backgrounds and unequal proficiency in English. In such conditions, the teacher must be very attentive to meet the needs of all students/learners and, at the same time, keep track of successes and failures in the designed study plans. One of the most notable reasons for subject/class failure and dropout, in a scenario such as the one described, is the performance and time dedication to written competence (Cabrera, 2014 & López Urdaneta, 2011). Consequently, we will explore whether the union of all the theoretical baggage that underpins the linguistic and pedagogical tradition of Error Analysis, one of the most notable tools for enhancing the writing competence of English as a Foreign Language, and new intelligent technologies can provide new perspectives and strategies to effectively help learners of English as a Foreign Language to produce more appropriate written texts (more natural outputs) and, at the same time, to check whether an AI-assisted Error Analysis-based assessment produces better results in error avoidance and rule application in the collected writing samples.

show abstract

Towards a Digital Assessment: Artificial Intelligence Assisted Error Analysis in ESL

Borrego

2023

Integr. J. Res. Arts Humanities

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Avoiding Algorithm Error in Computer-Aided Text Analysis: Selecting Text Analysis Software

Cited by 1 publication

References 0 publications

Towards a Digital Assessment: Artificial Intelligence Assisted Error Analysis in ESL

Towards a Digital Assessment: Artificial Intelligence Assisted Error Analysis in ESL

Contact Info

Product

Resources

About