“COMPARATIVE ANALYSIS BETWEEN PERCEPTIONS OF B-SCHOOL STUDENTS & ALUMNI ON SOFT SKILLS TRAINING IN ENHANCING EMPLOYABILITY COMPETENCY”
Abstract
Employability is described as all individual factors that influence the future positioning in a given segment of the labour market. The overall quality of students graduating from universities in India and abroad have found difficulty in satisfying expectations of business and industry. They have expressed their displeasure over quality of students being produced by the higher educational institutions. Management education is failing to grasp the enormous requirement of business and industry opportunities. There has been a severe gap between industry expectations and graduate skill sets (Hard & Soft Skills). Soft skills are essentially people skills and they complement hard skills. The sole purpose and aim of business schools in India and world over is to produce graduates who are instantly employable and productive. However, there seems to be a major gap between expectations of industry and university curriculum. This gap has led to unemployment. The main purpose of this study was to compare B-school students’ and alumni perceptions about the effect of soft skills training provided by B-Schools on their employability competency with reference to Bangalore.
Keyword : Employability Competencies, Graduate Skill Sets, Management Education, Soft Skills, Alumni
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
• Allen, Matthew., Dinham, Judith.et.al. (2020). “The Australian student voice on the soft skills needed for the future”, Retrieved on June 16, 2014 from https://www.oup.com.au/__data/assets/pdf_file/0024/172194/HE_Employability-Whitepaper_2020_DIGITAL_Singlepages.pdf. • Amballa, Lavanam., Mary, J Francis. (2016). “An examination on students’ perception of employability skills: Voice from non-engineering graduates in Coimbatore region, Tamilnadu”, International Journal of Business and Administration Research Review, vol. 1, issue 1, pp 277 – 281. • Badri, Shamsul Nizam. (2013). “Enhancing individual employability skills: A Case study of Universiti Teknologi Mara Pahang”, Retrieved on June 16, 2014 from http://etd.uum.edu.my. • Bradford, Jennifer. (2010). “Alumni perceptions of an employability focused curriculum”, Retrieved on April 06, 2015 from http://www.heacademy.ac.uk /sites/default/files/resources. • Creswell, John W.(2003). “Research Design: Qualitative, Quantitative and Mixed Method Approaches”, 2nd edition, New York: Sage Publications. • Fernandez, Rohan. (2021). “Role of soft skills in employability”, Retrieved on March 2023, from https://www.researchgate.net/publication/351613938. • Kaur, Tejbir., Dhillon, Jaskaran Singh., Bajwa, Rubeena. (2015). “What skills one needs to be employable?” – A Comparative study of perception of industry, students and faculty members from Punjab”, International Journal of Engineering Researches and Management Studies, vol. 2, issue 3, pp 2 -6. • Krejcie, Morgan. (1970). “Determining Sample Size for Research Activities”, Educational and Psychological Measurement, vol.30, pp. 607-610. • Lyons, Marlo. (2023). “5 Essential Soft Skills to Develop in Any Job”, Retrieved on January 16, 2023 from https://hbr.org/2023/02/5-essential-soft-skills-to-develop-in-any-job. • Peck, J., Theodore, N. (2000). “Beyond Employability”, Cambridge Journal of Economics, vol.24, issue 6, pp 729–749. • Ansarullah, S. I., Saif, S. M., Andrabi, S. A. B., Kumhar, S. H., Kirmani, M. M., & Kumar, D. P. (2022). An intelligent and reliable hyperparameter optimization machine learning model for early heart disease assessment using imperative risk attributes. Journal of Healthcare Engineering, 2022. https://doi.org/10.1155/2022/9882288. • Kumhar, S. H., Ansarullah, S. I., Gardezi, A. A., Ahmad, H., Abd Elgawad, A. E. E., & Shafiq, M. (2023). Translation of English Language into Urdu Language Using LSTM Model. Computers, Materials & Continua, 74(2), 3899-3912. https://doi.org/10.32604/cmc.2023.032290. • G. S. P. Ghantasala et al., "Tech-Enabled Banking Revolt:The Transformational Era of IT in the Financial Sector," 2023 Seventh International Conference on Image Information Processing (ICIIP), Solan, India, 2023, pp. 133-136, doi: 10.1109/ICIIP61524.2023.10537647. • Shaik, R. B., Banu, S. B., Siddiqui, S. A., Jyothi, M. K., Bhaumik, A., Chandini, S., & Aarif, M. (2023). Organizational Commitment Of Employee A Rising Risk In The Educational Sector. Boletin de Literatura Oral-The Literary Journal, 10(1), 2496-2505. • Banu, S. R., Banu, S. B., Shaik Chandini, D. V., Jyothi, M. K., & Nusari, M. S. (2022). Assessment of research skills in undergraduates students. Journal of Positive School Psychology, 6938-6948. • S. B. Banu, S. W. Akhtar, S. Arshad, S. R. Banu, S. Chandini and G. P. Ghantasala, "High Heels Are No More an Accessory of Fashion for Women- A Study Unrevealing the Health Effects of Wearing High Heels," 2024 10th International Conference on Communication and Signal Processing (ICCSP), Melmaruvathur, India, 2024, pp. 406-410, doi: 10.1109/ICCSP60870.2024.10543799. • Sahu, G., Anant, M., & Tiwari, S. The Impact of Social Media on the Positive Development of Teenagers in the Contemporary age • Sahu, G., Anant, M., Tiwari, S., & Gupta, T. C. (2024). SEZ-Led Economic Growth: Evaluating The Impact Of Export Promotion Policies On Developing Countries, With A Focus On India–An Analytical Study. Educational Administration: Theory and Practice, 30(4), 1215-1220. • Sahu, G., Anant, M., & Tiwari, S. (2023). Information and Communication Technology (ICT) in the context of Rural Women Empowerment. The journal of contemporary issues in business and government, 29(3), 323-329. • Sahu, G., Anant, M., & Tiwari, S. The Impact of Social Media on the Positive Development of Teenagers in the Contemporary age. • Malik, A., Gautam, S., Abidin, S., & Bhushan, B. (2019, July). Blockchain technology-future of IoT: including structure, limitations and various possible attacks. In 2019 2nd international conference on intelligent computing, instrumentation and control technologies (ICICICT) (Vol. 1, pp. 1100-1104). IEEE. • Abidin, S., Swami, A., Ramirez-Asís, E., Alvarado-Tolentino, J., Maurya, R. K., & Hussain, N. (2022). Quantum cryptography technique: A way to improve security challenges in mobile cloud computing (MCC). Materials Today: Proceedings, 51, 508-514. • Abidin, S., Vadi, V. R., & Rana, A. (2021). On confidentiality, integrity, authenticity, and Freshness (CIAF) in WSN. In Advances in Computer, Communication and Computational Sciences: Proceedings of IC4S 2019 (pp. 87-97). Springer Singapore. • Sucharitha, Y., Vinothkumar, S., Rao Vadi, V., Abidin, S., & Kumar, N. (2021). Wireless communication without the need for pre-shared secrets is consummate via the use of spread spectrum technology. J Nucl Ene Sci Power Generat Techno, 10(9), 2. • Abidin, S. (2019). Enhancing security in WSN by artificial intelligence. In International Conference on Intelligent Data Communication Technologies and Internet of Things (ICICI) 2018 (pp. 814-821). Springer International Publishing. • Bhoopathy, V., Behura, A., Reddy, V. L., Abidin, S., Babu, D. V., & Albert, A. J. (2021). WITHDRAWN: IOT-HARPSECA: A SECURE DESIGN AND DEVELOPMENT SYSTEM OF ROADMAP FOR DEVICES AND TECHNOLOGIES IN IOT SPACE. • Abidin, S. (2017). Greedy Approach for Optimizing 0-1 Knapsack Problem. Communications on Applied Electronics, 7(6), 1-3. • ajid, M., Jawed, M. S., Abidin, S., Shahid, M., Ahamad, S., & Singh, J. Capacitated Vehicle Routing Problem Using Algebraic Harris Hawks Optimization Algorithm. In Intelligent Techniques for Cyber-Physical Systems (pp. 183-210). CRC Press. • Abidin, S., Raghunath, M. P., Rajasekar, P., Kumar, A., Ghosal, D., & Ishrat, M. (2022, July). Identification of disease based on symptoms by employing ML. In 2022 International Conference on Inventive Computation Technologies (ICICT) (pp. 1357-1362). IEEE. • Malik, A., Parihar, V., Srivastava, J., Kaur, H., & Abidin, S. (2023, March). Prognosis of diabetes mellitus based on machine learning algorithms. In 2023 10th International Conference on Computing for Sustainable Global Development (INDIACom) (pp. 1466-1472). IEEE. • Vadi, V. R., Abidin, S., Khan, A., & Izhar, M. (2022). Enhanced Elman spike neural network fostered blockchain framework espoused intrusion detection for securing Internet of Things network. Transactions on Emerging Telecommunications Technologies, 33(12), e4634. • Abidin, S., Dhariwal, M. K., Rane, K. P., Sivakumar, G., Babu, D. V., & Kumar, I. R. (2021). Development and Organize of Wireless Sensor Network in Home Management using IoT. International Journal of Aquatic Science, 12. • Chadha, S., Mittal, S., & Singhal, V. (2020). Ancient text character recognition using deep learning. International Journal of Engineering Research and Technology, 3(9), 2177-2184. • Chadha, S., Mittal, S., & Singhal, V. (2019). An insight of script text extraction performance using machine learning techniques. International Journal of Innovative Technology and Exploring Engineering, 9(1), 2581-2588. • Gupta, N., Chauhan, R., & Chadha, S. (2020). Unmanned Aerial Vehicle (UAV) for Parcel Delivery. Int. J. Eng. Res. Technol, 13(10), 2824-2830. • Chadha, S., Chauhan, R., & Gupta, N. (2022). Flood Prediction And Rainfall Analysis Using LightGradient Boosted Machine. NeuroQuantology, 20(9), 1690. • Makkar, I. S., & Chadha, S. (2024, March). Unsupervised Emotion Matching for Image and Text Input. In 2024 IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI) (Vol. 2, pp. 1-6). IEEE. • Gupta, N., Chadha, S., Chauhan, R., & Singhal, P. (2023, December). Damage Evaluation Following Natural Disasters Using Deep Learning. In International Advanced Computing Conference (pp. 90-103). Cham: Springer Nature Switzerland. • Gupta, N., Chadha, S., Srivastava, G., & Chauhan, R. (2021, October). Mortality Rate Extrapolation Based on Symptomatic Symptoms of Novel Corona Virus. In 2021 5th International Conference on Information Systems and Computer Networks (ISCON) (pp. 1-5). IEEE. • ShikhaChadha, D. S., & Singhal, V. Ancient Text Character Recognition Using Deep Learning. • Verma, S., Gupta, N., Anil, B. C., & Chauhan, R. (2022). A Novel Framework for Ancient Text Translation Using Artificial Intelligence. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 11(4), 411-425. • Mandala, V. (2018). From Reactive to Proactive: Employing AI and ML in Automotive Brakes and Parking Systems to Enhance Road Safety. International Journal of Science and Research (IJSR), 7(11), 1992–1996. https://doi.org/10.21275/es24516090203 • Mandala, V. (2019). Optimizing Fleet Performance: A Deep Learning Approach on AWS IoT and Kafka Streams for Predictive Maintenance of Heavy - Duty Engines. International Journal of Science and Research (IJSR), 8(10), 1860–1864. https://doi.org/10.21275/es24516094655 • Mandala, V. (2019). Integrating AWS IoT and Kafka for Real-Time Engine Failure Prediction in Commercial Vehicles Using Machine Learning Techniques. International Journal of Science and Research (IJSR), 8(12), 2046–2050. https://doi.org/10.21275/es24516094823 • Mandala, V., & Surabhi, S. N. R. D. (2024). Integration of AI-Driven Predictive Analytics into Connected Car Platforms. IARJSET, 7(12). https://doi.org/10.17148/iarjset.2020.71216 • Mandala, V. Towards a Resilient Automotive Industry: AI-Driven Strategies for Predictive Maintenance and Supply Chain Optimization. • Mandala, V., & Surabhi, S. N. R. D. (2021). Leveraging AI and ML for Enhanced Efficiency and Innovation in Manufacturing: A Comparative Analysis. • Mandala, V. (2021). The Role of Artificial Intelligence in Predicting and Preventing Automotive Failures in High-Stakes Environments. Indian Journal of Artificial Intelligence Research (INDJAIR), 1(1). • Mandala, V., & Surabhi, S. N. R. D. Intelligent Systems for Vehicle Reliability and Safety: Exploring AI in Predictive Failure Analysis. • Mandala, V., & Kommisetty, P. D. N. K. (2022). Advancing Predictive Failure Analytics in Automotive Safety: AI-Driven Approaches for School Buses and Commercial Trucks. • Mandala, V., & Mandala, M. S. (2022). ANATOMY OF BIG DATA LAKE HOUSES. NeuroQuantology, 20(9), 6413. • Mandala, V., Premkumar, C. D., Nivitha, K., & Kumar, R. S. (2022). Machine Learning Techniques and Big Data Tools in Design and Manufacturing. In Big Data Analytics in Smart Manufacturing (pp. 149-169). Chapman and Hall/CRC. • Mandala, V. (2022). Revolutionizing Asynchronous Shipments: Integrating AI Predictive Analytics in Automotive Supply Chains. Journal ID, 9339, 1263. • Mandala, V., & Surabhi, S. N. R. D. (2024). Machine Learning Algorithms for Engine Telemetry Data: Transforming Predictive Maintenance in Passenger Vehicles. IJARCCE, 11(9). https://doi.org/10.17148/ijarcce.2022.11926 • Surabhi, S. N. R. D., Mandala, V., & Shah, C. V. AI-Enabled Statistical Quality Control Techniques for Achieving Uniformity in Automobile Gap Control. • Shah, C. V., Surabhi, S. N. R. D., & Mandala, V. ENHANCING DRIVER ALERTNESS USING COMPUTER VISION DETECTION IN AUTONOMOUS VEHICLE. • Mandala, V., Jeyarani, M. R., Kousalya, A., Pavithra, M., & Arumugam, M. (2023, April). An Innovative Development with Multidisciplinary Perspective in Metaverse Integrating with Blockchain Technology with Cloud Computing Techniques. In 2023 International Conference on Inventive Computation Technologies (ICICT) (pp. 1182-1187). IEEE. • Mandala, V., Rajavarman, R., Jamunadevi, C., Janani, R., & Avudaiappan, T. (2023, June). Recognition of E-Commerce through Big Data Classification and Data Mining Techniques Involving Artificial Intelligence. In 2023 8th International Conference on Communication and Electronics Systems (ICCES) (pp. 720-727). IEEE.