Mentoring G-SPACE Thesis and Dissertation Writers via Smart Technologies and Artificial Intelligence in a Blended Setting during COVID-19 Catastrophe

Autor/in	Bueno, David Cababaro
Titel	Mentoring G-SPACE Thesis and Dissertation Writers via Smart Technologies and Artificial Intelligence in a Blended Setting during COVID-19 Catastrophe
Quelle	3 (2020), S.1-14 (15 Seiten)Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Verfügbarkeit
Zusatzinformation	ORCID (Bueno, David Cababaro)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	2619-7820
Schlagwörter	Educational Technology; Artificial Intelligence; Blended Learning; Higher Education; Distance Education; Theses; Doctoral Dissertations; Mentors; Foreign Countries; Writing Evaluation; Grammar; Citations (References); Language Usage; Ethics; Graduate Students; Philippines + Suchen Sie Ihr Suchwort? Unterrichtsmedien; Künstliche Intelligenz; Hochschulbildung; Hochschulsystem; Hochschulwesen; Distance study; Distance learning; Fernunterricht; These; Doctoral dissertation; Doctoral thesis; Doctoral theses; Dissertationsschrift; Ausland; Grammatik; Citations; Zitat; Sprachgebrauch; Ethik; Graduate Study; Student; Students; Aufbaustudium; Graduiertenstudium; Hauptstudium; Studentin; Philippinen
Abstract	Recently, the impact of smart technologies and artificial intelligence as mechanisms for blended instruction in higher education institutions around the world has been of great interest. A cross-sectional design was used for this study. At a defined time, assumptions concerning the efficiency of a localized application of integrated smart technology and AI-mediated thesis and dissertation assessment during COVID-19 disaster came into play. The completed thesis and dissertation reports obtained by e-mail during March 2020 were first evaluated using the AI-tool to assess if the manuscript is ready for submission or requires minor or major revision. I have demonstrated how academic research mentors can contextualize and introduce a new e-mentoring approach. The AI-enhanced tool was highly effective in addition to being able to process initial evaluation in an average of 8 minutes per submission, with its special features and accurate enough to determine the accuracy of the language and references of a scientific study. Nonetheless, follow-up work can include plagiarism identification, abstract intelligence, journal scope checker and paper submission's technical compliance. (As Provided).
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01