Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Recurso digital |
| Sprache: | |
| Veröffentlicht: |
Zenodo
2026
|
| Online-Zugang: | https://doi.org/10.5281/zenodo.18885217 |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866901991816429568 |
|---|---|
| author | Kavita Ajay Joshi Lalit Singh Ravindra Koranga |
| author_facet | Kavita Ajay Joshi Lalit Singh Ravindra Koranga |
| contents | <div> <p><span>This empirical research presents a new AI-Natural Language Processing (NLP) workshop model, which synergistically combines Ennegram personality typology, PERMA wellbeing model (Positive Emotion, Engagement, Relationships, Meaning, Accomplishment) and SWOC analysis (Strengths, Weaknesses, Opportunities, Challenges) and eliminates the fear of privacy encroachment and discrimination inhibitions inherent in conventional MBA mentor-mentee programs. In a study involving 100 prefinal-year students of Graphic Era Hill University, using conventional facilitator-led practices, only 25% of high performers in 10 parameters that are most relevant in relation to placement e.g. strategic thinking, drive, communication skills, empathy/emotional intelligence, decision-making, adaptability/resilience, influence and persuasion (critical 5/100 high performers), willingness to learn, ethical behavior and collaboration/teamwork were obtained because of unwillingness to make authentic Enneagram self-discloser. The AI intervention provided privacy-preserving customization: Ennegram typing based on the self-evaluation, formal assessment, or conversation transcripts, PERMA improvement through the sentiment analysis (positive emotions), gamified interaction, practice with chatbots in relation practice, narrative generation of meaning, automated SWOC matrix generation on mixed MCQ/subjective quizzes using generative AI. An automated 45 minutes workflow with legal awareness (POSH Act 2013 quiz on Section 2(n) harassment definitions, ICC formation, 90-day timelines; Article 21 privacy rights; DPDP Act 2023 compliance) and dramatic results were achieved: 89% high performers after the workflow (Tables 1-2), with 65.3% increment on average with influence and persuasion in a sharp rise of 80% (5-85) (surging). The AI-traditional comparisons of Fig 1 visualization prove the superiority of AI over classical methods not only to address the ethical issues (AI-NLP bias, data breaches, explainability) but also to provide a scalable edtech model to support student wellbeing, legal literacy, and corporate preparedness as stipulated by Mental Healthcare Act 2017. </span></p> </div> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18885217 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | The Enneagram, PERMA, and SWOC: AI-Based Workshops to improve MBA Employability by Overcoming the Privacy barriers with legal sentience in colloquial vogue. Kavita Ajay Joshi Lalit Singh Ravindra Koranga <div> <p><span>This empirical research presents a new AI-Natural Language Processing (NLP) workshop model, which synergistically combines Ennegram personality typology, PERMA wellbeing model (Positive Emotion, Engagement, Relationships, Meaning, Accomplishment) and SWOC analysis (Strengths, Weaknesses, Opportunities, Challenges) and eliminates the fear of privacy encroachment and discrimination inhibitions inherent in conventional MBA mentor-mentee programs. In a study involving 100 prefinal-year students of Graphic Era Hill University, using conventional facilitator-led practices, only 25% of high performers in 10 parameters that are most relevant in relation to placement e.g. strategic thinking, drive, communication skills, empathy/emotional intelligence, decision-making, adaptability/resilience, influence and persuasion (critical 5/100 high performers), willingness to learn, ethical behavior and collaboration/teamwork were obtained because of unwillingness to make authentic Enneagram self-discloser. The AI intervention provided privacy-preserving customization: Ennegram typing based on the self-evaluation, formal assessment, or conversation transcripts, PERMA improvement through the sentiment analysis (positive emotions), gamified interaction, practice with chatbots in relation practice, narrative generation of meaning, automated SWOC matrix generation on mixed MCQ/subjective quizzes using generative AI. An automated 45 minutes workflow with legal awareness (POSH Act 2013 quiz on Section 2(n) harassment definitions, ICC formation, 90-day timelines; Article 21 privacy rights; DPDP Act 2023 compliance) and dramatic results were achieved: 89% high performers after the workflow (Tables 1-2), with 65.3% increment on average with influence and persuasion in a sharp rise of 80% (5-85) (surging). The AI-traditional comparisons of Fig 1 visualization prove the superiority of AI over classical methods not only to address the ethical issues (AI-NLP bias, data breaches, explainability) but also to provide a scalable edtech model to support student wellbeing, legal literacy, and corporate preparedness as stipulated by Mental Healthcare Act 2017. </span></p> </div> |
| title | The Enneagram, PERMA, and SWOC: AI-Based Workshops to improve MBA Employability by Overcoming the Privacy barriers with legal sentience in colloquial vogue. |
| url | https://doi.org/10.5281/zenodo.18885217 |