000			03051nam a22002537a 4500
999			_c83248 _d83248
003			20221105103337.0
005			20230321174818.0
008			221105b ||||| |||| 00| 0 eng d
041			_aeng
082			_a658.31124
100	1		_aBacalso, Patrick Lape _eauthor
245	1	0	_aCUTIE : _bCIT-University tutoring interviewer environment / _cby Patrick Lape Bacalso
300			_aix, 47 leaves : _bcolor illustrations; _c28 cm
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
502			_aThesis (DIT) -- Cebu Institute of Technology - University, _dDecember 2021
504			_aIncludes bibliographical references (pages 13-14).
520			_aThis study aims to develop a socio-technical model named CUTIE: CIT University Tutoring Interviewer Environment that improve self-presentation during a job interview for students of Cebu Institute of Technology University by using effective technological tools that can help close the gap in developing this emerging skills. The first phase of the study was to ideate the design of our life-like interview simulator (CUTIE) using the concepts in Design Thinking and Human-Computer Interaction. The main objective of this phase is to analyze the effectivity of our foundational elements of CUTIE using a 3D human-like interviewer, Sentiment analysis using audio and video input, adaptive interview questions taken from Society of Human Resource Management and Virtual Background Setting. A system prototype was handed to respondents in selecting virtual interviewer as a preference based on a different persona within the university. Data were collected through interview and survey using the methods on Reliability Analysis and Exploratory Factor Analysis to identify six attributes of engagement: Perceived Usability, Aesthetics, Focused Attention, Felt Involvement, Novelty and Endurability. The result was very satisfactory. After the receiving positive feedbacks form our Ideation phase, we move forward to the next phase on the development of this project by implementing the foundation elements of CUTIE using open-sourced application software that match our requirements like Vue.js as our Web Client, GraphQ1 for Data Query and Manipulation and Django as our CUTIE Server for initial deployment of the program. The bot performs real-time analysis of the sentiment and the emotional response of the student. The study started by analyzing of the sentiment and the emotional response of the student. The study started by analyzing 114 videos of students submitted as answers to an interview questionnaire. The videos were then manually analysed by experts for scoring. The current model shows encouraging results in terms of facial recognition and sentiment analysis. It also contributed by identifying factors that could affect the result of video analysis used for validation test.
650		0	_aEmployment interviewing.
650		0	_aHuman-computer interaction
655		0	_aAcademic theses.
942			_2ddc _cT&D