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Artykuły w czasopismach na temat „Mock Interview”

Autor: Grafiati

Data publikacji: 2 czerwca 2025

Data aktualizacji: 31 lipca 2025

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Padmaja, K., Apoorva S. Bhat, Esther J. Kenn, and Jeevitha L. Prakash. "MOCK INTERVIEW SYSTEM." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 12 (2024): 1–6. https://doi.org/10.55041/ijsrem40009.

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Abstract -Sconti-AI is an innovative platform revolutionizing exam preparation and interview practice by harnessing advanced AI technology. It offers detailed feedback, scores, and explanations for mock tests, optimizing learning outcomes and improving performance. Its standout feature, a mock interview tool, uses Generative AI and image recognition to detect cheating, analyze emotional responses, and provide personalized insights for better interview preparation. Built with robust technologies like React, Python- Flask, and Gemini-AI, the platform ensures scalability, reliability, and user en

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Thawali, Bharati, Pranjal Kalal, Samarth Dugam, and Harshada Lokhande. "EmoConfident Interviewer :An AI Mock Interview Evaluator." International Journal for Research in Applied Science and Engineering Technology 12, no. 6 (2024): 846–52. http://dx.doi.org/10.22214/ijraset.2024.63173.

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Abstract: Interviews hold great significance for candidates as it's the moment when their hard work is put to the test in hopes of achieving their desired and successful life results. It plays a crucial role in our educational system and hiring process by helping to identify the best applicant based on the necessary abilities. We can do better by improving our communication and confidence skills through mock interviews. This article introduced new way to practice for interviews using AI-based mock interview platform. The three characteristics that our system will utilize to evaluate the user a

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Patil, Vitthal. "AI Mock Interview Platform." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–9. https://doi.org/10.55041/ijsrem49510.

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Abstract - The demand for effective interview preparation solutions has surged as job seekers seek comprehensive and interactive ways to enhance their readiness. The Full Stack AI Mock Interview App leverages cutting-edge technologies, including Next.js, Drizzle ORM, and AI integration, to provide a robust platform for dynamic interview practice. By integrating GPT-3 for question and answer generation, users receive personalized and adaptive interview experiences tailored to various job roles and industries. The app's ability to allow users to record their answers via webcam and microphone sim

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Journal, IJSREM. "AI Mock Interviewer: Preparing You Towards Smarter Interview Practice." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 01 (2024): 1–10. http://dx.doi.org/10.55041/ijsrem28199.

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In today's fiercely competitive job market, interview performance plays a pivotal role in securing employment. However, candidates often face the challenge of limited access to personalized and realistic interview practice opportunities, hindering their confidence-building efforts. To address this gap, we propose an AI-powered mock interviewer web application that creates an interview environment for candidates and elevates their interview preparation. The web app extracts vital information from user-uploaded resumes using Google's Palm model and Textract, crafting interview questions customiz

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G.Ramachandra, Rao, Chakradhar Reddy Bijjamula, Srinivas Kalyan Anne, Keerthi Priya Goli, and Rajesh Kanakamedala. "AI-Powered Mock Interview Preparation." International Journal for Modern Trends in Science and Technology 11, no. 04 (2025): 65–70. https://doi.org/10.5281/zenodo.15108980.

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The Mock Interview System is an innovative, AI-driven platform designed to address the challenges faced by candidates preparing for interviews in today’s competitive job market. In many instances, interview preparation is hindered by a lack of practical, role-specific practice and meaningful feedback, which can lead to anxiety and subpar performance during actual interviews. This project proposes a solution that not only simulates real-world interview conditions but also offers personalized feedback to help candidates improve both technical and behavioral skills.The core objective of the

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Koenigsfeld, Carrie F., Geoffrey C. Wall, Andrew R. Miesner, et al. "A Faculty-Led Mock Residency Interview Exercise for Fourth-Year Doctor of Pharmacy Students." Journal of Pharmacy Practice 25, no. 1 (2012): 101–7. http://dx.doi.org/10.1177/0897190011431632.

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Purpose: To determine whether a faculty-led mock-interview activity enhanced pharmacy student preparation for the residency interview process and increased match rates. Methods: Twenty-eight doctor of pharmacy students volunteered for a 40-minute mock-interview session with 2-person faculty teams. A standard roster of 12 interview questions was derived from published literature and the faculty members’ experience. Feedback on the student’s interview performance was provided verbally during the session. Following the interview, students were given a 2-part survey instrument. The first part of t

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Marks, Melanie, and Abigail H. O’Connor. "The Round-Robin Mock Interview." Business Communication Quarterly 69, no. 3 (2006): 264–75. http://dx.doi.org/10.1177/1080569906291257.

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Lyle, Timothy S. "An Interview with Janet Mock." Callaloo 38, no. 3 (2015): 502–8. http://dx.doi.org/10.1353/cal.2015.0099.

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Kolpe, Prof Sakharam. "AI Based Mock - Interview Behavioural Recognition Analyst." International Journal for Research in Applied Science and Engineering Technology 12, no. 5 (2024): 3654–66. http://dx.doi.org/10.22214/ijraset.2024.61427.

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Abstract: In Present competitive job market hustle, being skilled at interview skills is very vital for current institution graduates looking for further trainings or hiring opportunities. Yet, several Interview Candidates needs suitable preparation for interview situations throughout candidate institute academic years. To discourse this opening, scholars have aims on designing and development of societal skills training classifications to offer candidates with opportunities to boost the interview skills. Job interviews assist as a fundamental means for potential employers to evaluate candidat

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Marcus, Jessica A., Laura DeMars, Chip Zimmerman, et al. "Evaluating the Effectiveness of a Virtual Mock Interview for Health Professions Students." Journal of Nursing Education 62, no. 8 (2023): 479–82. http://dx.doi.org/10.3928/01484834-20230612-10.

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Background: Virtual mock interviews were offered to students to improve job interviewing skills. This educational quality improvement project aimed to use virtual mock interviews to increase student preparedness and confidence, and reduce anxiety related to professional interviews. Method: Health professions students ( n = 19) participated in the mock interviews conducted and recorded through a web-based meeting. Students received the recorded interview to watch before follow-up. Students completed pre- and postquestionnaires that addressed students' preparedness, confidence, and anxiety relat

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Wadne, Dr Vinod S. "AI-Powered Interview Xpert: An Intelligent Platform for Interviews, Resumes, and Portfolios." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem48010.

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In the modern job market, standing out requires more than just qualifications—it demands excellent interview skills, strong resumes, and an impressive portfolio. This project introduces an AI-powered platform aimed at helping job seekers and students excel in these critical areas. The platform combines three key components: a Mock Interview Assistant, a Resume Generator, and a Portfolio Creator—each enhanced with artificial intelligence to deliver tailored feedback and data-driven support. The Mock Interview module simulates realistic interview environments by customizing questions based on th

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Buckley, Kelsey, Samantha Karr, Sarah A. Nisly, and Kristi Kelley. "Evaluation of a mock interview session on residency interview skills." Currents in Pharmacy Teaching and Learning 10, no. 4 (2018): 511–16. http://dx.doi.org/10.1016/j.cptl.2017.12.021.

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Gupta, Neha, Aashi Sharma, Suneet Shukla, and Praveen Kumar. "AI-based mock interview evaluator: An emotion and confidence classifier model." International Journal of Research in Engineering and Innovation 09, no. 03 (2025): 136–42. https://doi.org/10.36037/ijrei.2025.9308.

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In today’s highly competitive job market, interview preparedness has become more critical than ever. Traditional mock interviews often lack scalability, objectivity, and actionable insights. To address these limitations, this paper proposes an AI-Based Mock Interview Evaluator that combines emotion recognition and confidence classification to assess candidate performance. Using facial expression analysis and speech feature extraction, the system offers real-time feedback on emotional state and confidence level during simulated interview sessions. The model leverages Convolutional Neural Networ

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Uparkar, Swati. "IntelliView: An AI Based Mock Interview Platform." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem31356.

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The IntelliView initiative represents a pioneering endeavor designed to empower novice job seekers through the integration of state-of-the-art Artificial Intelligence (AI) and Natural Language Processing (NLP) technologies. This platform employs a sophisticated blend of HTML, CSS, JavaScript, and the Deep Face method, introducing a comprehensive framework to redefine interview assessment and augment job application preparation. The primary module facilitates text-based analysis, enabling users to engage with real-time interview questions by entering responses directly into the web interface. S

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Journal, IJSREM. "IntelliView: An AI Based Mock Interview Platform." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 03 (2024): 1–11. http://dx.doi.org/10.55041/ijsrem29201.

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The IntelliView initiative represents a pioneering endeavor designed to empower novice job seekers through the integration of state-of-the-art Artificial Intelligence (AI) and Natural Language Processing (NLP) technologies. This platform employs a sophisticated blend of HTML, CSS, JavaScript, and the Deep Face method, introducing a comprehensive framework to redefine interview assessment and augment job application preparation. The primary module facilitates text-based analysis, enabling users to engage with real-time interview questions by entering responses directly into the web interface. S

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Abdul Rahim, Salmiza, and Lam Kok Wei. "STUDENT’S PERCEIVED COMPETENCE IN MOCK JOB INTERVIEWS." PUPIL: International Journal of Teaching, Education and Learning 9, no. 1 (2025): 59–71. https://doi.org/10.20319/pijtel.2025.91.5971.

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With the increasing importance of English proficiency in Malaysia’s competitive job market—particularly in interview settings—this research investigates students’ self-perceptions of their readiness and abilities after participating in simulated job interviews. A total of 36 students took part in the study by completing a self-evaluation questionnaire. The findings reveal that while students generally perceived themselves as prepared, especially in areas such as appearance, non-verbal cues, and basic interview etiquette, there was a noticeable gap in their perceived performance, particularly i

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R, Mr Madanachitran. "AI Mock Interview Chatbot Using Gen AI." International Journal of Science, Engineering and Technology 13, no. 2 (2025): 1–9. https://doi.org/10.61463/ijset.vol.13.issue2.189.

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Ahmed, Bilal, Victoria Ly, Ankur Parikh, et al. "Perceptions of a Virtual Interview Exercise for Ophthalmology Residency Applicants." Journal of Academic Ophthalmology 13, no. 02 (2021): e256-e263. http://dx.doi.org/10.1055/s-0041-1733939.

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Abstract Importance In-person interviews have traditionally been considered a crucial component of the residency application process. Virtual interviews (VIs) became the standard format for the 2020 to 2021 application cycle due to the novel coronavirus disease 2019 (COVID-19) pandemic. VIs offer a new perspective and challenge to this process which warrants unique considerations and further understanding of effects on applicants. Objective This study aimed to assess the perceived efficacy of a VI preparedness exercise for ophthalmology residency applicants in the 2021 residency application cy

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Patil, Pankaj Rambhau. "Elevating Performance Through AI-Driven Mock Interviews." International Journal for Research in Applied Science and Engineering Technology 12, no. 6 (2024): 1136–39. http://dx.doi.org/10.22214/ijraset.2024.63277.

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Abstract: This paper proposes an innovative AI-based mock interview platform designed to enhance interview preparedness by assessing candidates across three key dimensions: emotions, confidence, and knowledge. Utilizing deep learning convolutional neural networks, the system analyzes facial expressions to gauge emotional responses, while speech recognition and natural language processing evaluate the candidate's confidence levels. Additionally, semantic analysis and keyword mapping assess the candidate's knowledge by comparing responses with relevant online resources. This comprehensive approa

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Collin, Winnie. "“It was probably that guy?” – The functions of reconstructive speech acts in investigative training interviews." Scandinavian Studies in Language 11, no. 1 (2020): 170–95. http://dx.doi.org/10.7146/sss.v11i1.121365.

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This paper explores the pragmatic and interactional functions of reconstructive speech acts in mock police interviews, based on a model of argumentative dialogue. The aim of the paper is to illustrate how the reconstructions apparently contribute to both the interaction between the police officer and the mock suspect in the interview activity and to the interaction in the training activity, i.e. between the participants attending the training course. Drawing on functional pragmatics and grammar, the analysis seeks to examine how reconstructions on the one hand function in the socially non-coop

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Caballero, Joshua, Sandra Benavides, Kevin A. Clauson, et al. "Role of Residency Interview Preparatory Activities as a Determinant on Pharmacy Residency Match Rates." Journal of Pharmacy Practice 30, no. 2 (2016): 219–22. http://dx.doi.org/10.1177/0897190016632127.

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Purpose: Different strategies have been implemented to assist students in securing residency positions. The purpose of this study was to explore the impact of student participation in residency preparation activities on match rates. Methods: A retrospective observational study was conducted to explore the effect of participation in residency preparation activities and grade point average (GPA) on residency match rate. Match rates for students participating in the Residency Interview Preparation Seminar (RIPS) or mock interviews (ie, intervention group) were compared with students who participa

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Kumazaki, Hirokazu, Taro Muramatsu, Yuichiro Yoshikawa, et al. "Job interview training targeting nonverbal communication using an android robot for individuals with autism spectrum disorder." Autism 23, no. 6 (2019): 1586–95. http://dx.doi.org/10.1177/1362361319827134.

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Job interviews are significant barriers for individuals with autism spectrum disorder because these individuals lack good nonverbal communication skills. We developed a job interview training program using an android robot. The job interview training program using an android robot consists the following three stages: (1) tele-operating an android robot and conversing with others through the android robot, (2) a face-to-face mock job interview with the android robot, and (3) feedback based on the mock job interview and nonverbal communication exercises using the android robot. The participants

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M Khadar, Firdouziya, Devika G. Devika G, Nayana Liz Mathews, Parvathy R. Prasad, and Sulaja Sanal. "A Comprehensive Survey on Mock Interview Evaluation Systems." International Journal of Advances in Engineering and Management 06, no. 12 (2024): 71–74. https://doi.org/10.35629/5252-06127174.

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—Interviews are essential for evaluating candidates’ skills, knowledge, and suitability for job roles, while mock interviews serve as valuable tools for preparation. With rapid advancements in artificial intelligence (AI) and machine learning (ML), automated interview evaluation has transformed recruitment by offering more objective, efficient, and comprehensive assessments compared to traditional methods. This survey re- views recent AI-driven methodologies for candidate evaluation in mockinter view settings, focusing on multi-modal techniques such as facial emotion recognition, speech analys

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Multerer, Sara, Becky Carothers, Pradip D. Patel, Craig Ziegler, Michael Rowland, and Deborah Winders Davis. "Senior Medical Student Mock Interview Program in Pediatrics." Southern Medical Journal 109, no. 2 (2016): 101–6. http://dx.doi.org/10.14423/smj.0000000000000416.

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Rikard, G. Linda, and Terry A. Senne. "A Mock Interview Preservice Teachers and Principals Interact." Journal of Physical Education, Recreation & Dance 67, no. 3 (1996): 16–17. http://dx.doi.org/10.1080/07303084.1996.10607215.

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N, Sasikumar. "AI-Powered Opportunity Crafter: Unlocking Smart Career Possibilities." International Journal for Research in Applied Science and Engineering Technology 13, no. 4 (2025): 5032–37. https://doi.org/10.22214/ijraset.2025.68844.

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The job market is highly competitive, making it challenging for job seekers, including students, fresh graduates, and professionals, to secure employment. Traditional job search methods lack efficiency, personalization, and real-time feedback, often leaving candidates unprepared for Applicant Tracking Systems (ATS) and interviews. To address these challenges, we propose an AI-Powered Opportunity Crafter, an intelligent job assistant that leverages Artificial Intelligence (AI), Natural Language Processing (NLP), and Machine Learning (ML) to enhance job seekers' success rates., The system consis

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Lakshmi, Mrs N. Bhagya. "Advanced Interview Skills Development and Personalized Mentorship: Achieving Interview Excellence." International Journal for Research in Applied Science and Engineering Technology 13, no. 4 (2025): 5877–81. https://doi.org/10.22214/ijraset.2025.69686.

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The current job landscape makes interviews essential for assessing candidates' abilities and fit with potential employers. However, many applicants experience anxiety due to a lack of preparation and ineffective self-presentation. To address these issues, we introduce a Generative AI-based interview preparation platform that offers customized mock interviews in both voice and text formats. The system includes adaptive practice, realistic simulations, comprehensive feedback, performance analytics, and user-friendly access, all working together to enhance candidates' interview readiness.

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White, Charles S. "Role-Played Relationships between Assertiveness and Mock Interviewing Success." Psychological Reports 59, no. 2 (1986): 563–69. http://dx.doi.org/10.2466/pr0.1986.59.2.563.

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122 undergraduate business and psychology students conducted mock screening interviews in a laboratory setting. Interviewees' assertiveness was associated with this interviewing success. The interviewers' assertiveness was unrelated to interview success.

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Abin, Idicula Benny John, ChristoEldhose, Shaju Eldho, Jaimon Parvathi, and Skaria Teena. "Mock AI Interviewer for Real-Time Feedback and Suggestion." Recent Trends in Androids and IOS Applications 7, no. 2 (2025): 20–30. https://doi.org/10.5281/zenodo.15421829.

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<em>The "Mock AI Interviewer for Real-Time Feedback and Suggestions" is an advanced AI-driven interview training system designed to transform the way candidates prepare for interviews by providing instant, data-driven feedback. Traditional interview preparation often lacks personalized insights and relies on subjective evaluation, leaving candidates uncertain about their strengths and areas for improvement. This system bridges that gap by analyzing both verbal and non-verbal cues— including speech patterns, grammatical accuracy, emotional expressions, and confidence levels—to gener

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Dr. J. M. Patil, Eisha Nikam, Samruddhi Katole, Sanika Dose, and Vaishnavi Avadhut. "Eloqify: Intelligent Interview Companion." International Research Journal on Advanced Engineering Hub (IRJAEH) 3, no. 03 (2025): 786–91. https://doi.org/10.47392/irjaeh.2025.0110.

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In today’s highly competitive job market, securing a technical role requires rigorous preparation and real-time feedback. Eloqify is an AI-driven mock interview platform exclusively designed for technical interviews, helping candidates refine their core skills through interactive and unbiased assessments. Our platform leverages Google Gemini AI to dynamically generate technical interview questions based on resume parsing, ensuring that candidates practice with job-specific, industry-relevant questions. The resume parsing, powered by Python-based processing, extracts key skills and experiences,

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Bhute, Dr Harsha A. "MockMate: AI-Powered Online Mock Interview Assessment and Evaluation System." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem45858.

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Abstract: In the current competitive job market, being well-prepared for interviews is essential to landing a job. Traditional mock interviews, however, are not scalable and can call for a large human resource commitment. By providing a tailored, automated, and interactive online platform driven by artificial intelligence, MockMate tackles this problem. The system mimics actual interview situations, assesses candidate responses in real time, and provides thorough, data-driven feedback by utilizing cutting-edge Natural Language Processing (NLP) and speech-to-text technologies. In addition to cu

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Mani, Sudha, Prabakar Kothandaraman, Rajiv Kashyap, and Bahar Ashnai. "Sales Role-Plays and Mock Interviews." Journal of Marketing Education 38, no. 3 (2016): 183–98. http://dx.doi.org/10.1177/0273475315606785.

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Sales competitions provide students with opportunities to apply their understanding of sales. Despite a long tradition of scholarship on sales role-plays, the answer to what drives student performance in sales competitions remains elusive. In this research, we examine how motivation (work engagement) and ability (cognitive aptitude and selling-related knowledge) affect student performance in sales role-play competitions. We also examine how success in sales role-plays engenders job attainment for the students. Using data from a sales competition held at a large public university in the United

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Powell, Amanda D., Sikeat Yip, Jeremy Hillman, Suzanne Larson, Janet Cooley, and Lindsay E. Davis. "Preparing pharmacy graduates for interviews: A collaborative statewide mock interview session to improve confidence." Currents in Pharmacy Teaching and Learning 7, no. 5 (2015): 684–90. http://dx.doi.org/10.1016/j.cptl.2015.06.009.

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Shin, Chung, and Park. "Detection of Emotion Using Multi-Block Deep Learning in a Self-Management Interview App." Applied Sciences 9, no. 22 (2019): 4830. http://dx.doi.org/10.3390/app9224830.

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Recently, domestic universities have constructed and operated online mock interview systems for students’ preparation for employment. Students can have a mock interview anywhere and at any time through the online mock interview system, and can improve any problems during the interviews via images stored in real time. For such practice, it is necessary to analyze the emotional state of the student based on the situation, and to provide coaching through accurate analysis of the interview. In this paper, we propose detection of user emotions using multi-block deep learning in a self-management in

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Hemrajani, Reena H., Karen L. Law, Tiffany A. Walker, and Danielle Jones. "Preparing Residents for Fellowship: A Novel Mock Interview Program." Southern Medical Journal 115, no. 7 (2022): 395–99. http://dx.doi.org/10.14423/smj.0000000000001412.

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Chaugule, Balaji. "HireIQ - AI-Based Mock Interview Platform with Behavioral Analysis." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem48228.

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Abstract - This initiative is concerned with the creation of an AI-based platform for conducting job interviews that utilizes both technical assessment and behaviour analysis. The system enables candidates to respond to questions through video, where their responses and behaviours are analysed using advanced technology. Their verbal responses are processed using speech recognition tools and their content assessed for technical accuracy and communications by natural language processing models. Computer vision is used by the platform to evaluate non-verbal like their facial expressions and postu

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Lim, Mei. "Enhancing Student Employability Through Authentic Assessment." Environment-Behaviour Proceedings Journal 9, no. 29 (2024): 149–53. http://dx.doi.org/10.21834/e-bpj.v9i29.6020.

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This study explores the implementation of authentic assessment to enhance student employability through participating in interviews with real-world employers. Industry-leading employers conduct mock interviews with students to allow them to sharpen their interview skills and assist in understanding the expectations of prospective employers. A key finding of the study is that students who are equipped with the necessary training for interview skills and career development learning will gain confidence and self-esteem, fitted with both interview and soft skills, hence preparing them for answerin

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Blumenstein, Nicole Rose, David Mendel Bruss, Krystal Kan, and Jeffrey Yu. "PGY1 Resident-Led Mock Virtual Interviews to Prepare for the 2022 Otolaryngology Residency Virtual Interviews." OTO Open 5, no. 4 (2021): 2473974X2110679. http://dx.doi.org/10.1177/2473974x211067947.

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Due to the ongoing coronavirus disease 2019 pandemic, virtual interviews are planned for the 2021-2022 residency application cycle. The virtual interview will remain novel to applicants for each match cycle until the graduating medical student class has experience from virtual interviews during their medical school admissions. The virtual interview poses unique challenges that are unique from in-person formats. Given the lack of experience of applicants in the 2022 match, practicing interviewing skills prior to the actual date is vital to success. We describe a postgraduate year 1 (PGY1)–run m

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Thafsil, Rahman. K. M., Abilesh Kumar. T. Sri, S. Sakthinathan., and Priya. A. Mohana. "Career Tracking." International Journal of Trend in Scientific Research and Development 2, no. 3 (2018): 1626–28. https://doi.org/10.31142/ijtsrd11453.

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Now a days, filtering the students for the placement drive is too difficult task to manage the student's record. To overcome these difficulties the concept CAREER TRACKING is implemented. It is to track the student's eligibility to attend the Recruitment process of company, based on their attendance, Mock Periodical Technical Test and Mock Periodical Aptitude Test percentage. In this web application we will have the database of the companies which came to our college which includes company's package's, sample interview question which have been asked in the last recruitment. Als

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Brubacher, Sonja P., Martine Powell, Helen Skouteris, and Belinda Guadagno. "An Investigation of the Question-Types Teachers Use to Elicit Information From Children." Australian Educational and Developmental Psychologist 31, no. 2 (2014): 125–40. http://dx.doi.org/10.1017/edp.2014.5.

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Background: Teachers are required to report suspected child abuse in many parts of the world, but there is a paucity of research characterising how they question children about wrongdoing. Aims: Because children often speak to multiple people before arriving at a forensic interview it is critical to understand how untrained teachers question children. Sample and Methods: Teachers (n = 47) completed a mock interview, written quiz, and rated their expected performance. Results: In both the interview and quiz, teachers asked few open and many leading questions. Yet, they asked proportionally more

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Waterhouse, Genevieve F., Anne M. Ridley, Ray Bull, and Rachel Wilcock. "Mock-juror reactions to multiple interview presentation and rapport-building." Psychology, Crime & Law 26, no. 2 (2019): 186–205. http://dx.doi.org/10.1080/1068316x.2019.1652745.

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Polaha, Jodi, Ivy Click, Brian Cross, Adam Welch, Rick Hess, and Jessica Burchette. "A mock job interview to assess an interprofessional education program." Journal of Interprofessional Education & Practice 15 (June 2019): 94–99. http://dx.doi.org/10.1016/j.xjep.2019.03.001.

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McBurney, Patricia G. "Commentary on “Senior Medical Student Mock Interview Program in Pediatrics”." Southern Medical Journal 109, no. 2 (2016): 107. http://dx.doi.org/10.14423/smj.0000000000000417.

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Powell, Martine B., Carolyn H. Hughes-Scholes, Cristina Cavezza, and Mark A. Stoové. "Examination of the stability and consistency of investigative interviewer performance across similar mock interview contexts." Legal and Criminological Psychology 15, no. 2 (2010): 243–60. http://dx.doi.org/10.1348/135532509x472077.

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Awasare, Siddhi. "Prepmania: an AI-Powered Mock Interview Platform for Skill Evaluation and Performance Feedback." International Journal for Research in Applied Science and Engineering Technology 13, no. 5 (2025): 3461–70. https://doi.org/10.22214/ijraset.2025.70977.

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Prepmania is an AI-powered mock interview platform designed to help job seekers prepare effectively for real interviews. The name combines "Preparation" and "Mania," reflecting a passionate, focused approach to interview readiness. The system generates role-specific questions based on user inputs like job title, skills, and experience. A key innovation is its multimodal analysis—using facial expression recognition and voice analysis to assess confidence, communication, and behavior. Prepmania enhances preparation through AI-powered feedback, response comparison, and visual performance analytic

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haris H, Abdul. "Advancing Interview AI-Driven Real-Time Mock Interview System for Enhanced Communication and Technical Skills." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 03 (2025): 1–9. https://doi.org/10.55041/ijsrem42280.

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The machine learning-based mock interview system allows candidates to practice technical, non-technical, and group discussion sessions through a virtual platform. It uses sentiment analysis, emotion detection, and grammar checking to evaluate candidates' performance. The technical session assesses the use of correct technical terms, while the non-technical session grades emotional expression, grammar, and filler words. Group discussions are hosted on the Agora platform for real-time interaction. The system provides personalized feedback and recommendations for improving both communication and

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Walavalkar, Rajaram Bharat, Siddhant Dinesh PasiSiddhant Dinesh Pasi, Harsh Sanjiv Pandey, Meet Manish Parmar, and Silviya D’monte. "HireVision.AI." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 01 (2025): 1–9. https://doi.org/10.55041/ijsrem40313.

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HireVision.AI is an AI-powered interview preparation platform designed to revolutionize how users prepare for job interviews. By leveraging the power of artificial intelligence, this platform offers a comprehensive and user-friendly solution that addresses the common challenges faced by candidates during the interview process. With AI-driven mock interviews simulating real-life scenarios, users can practice and receive personalized feedback regarding their performance. This feedback not only highlights areas of improvement, but also boosts candidates' confidence, ensuring that they are better

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Izotovas, Aleksandras, Aldert Vrij, Leif A. Strömwall, and Samantha Mann. "Facilitating Memory-Based Lie Detection in Immediate and Delayed Interviewing: The Role of Sketch Mnemonic." Psichologija 61 (October 2, 2020): 68–89. http://dx.doi.org/10.15388/psichol.2020.16.

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Memory enhancing techniques, or mnemonics, are typically recommended in evidence-based investigative interviewing guidelines. In the current study, the use of a sketch mnemonic and its effect on the responses of truth tellers and liars was examined. Participants (n = 49) watched a mock intelligence operation video. They were instructed to tell the truth or lie about this operation in an interview immediately afterwards, and again after a two-week delay. In both interviews participants were requested to make a sketch of the place of the mock operation, and then to verbally describe the drawing.

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Ulbrich, David J. "The First Mock Interview Sessions: Conference Report: Student Affairs." Historically Speaking 2, no. 1 (2000): 14–15. http://dx.doi.org/10.1353/hsp.2000.0016.

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Haar, Shannon S., Song Oh, Rebecca Munger, Diane H. Quinn, and Thaddeus McGiness. "Delivery of a Virtual Residency Mock Interview Experience to Student Pharmacists." American Journal of Pharmaceutical Education 88, no. 9 (2024): 100962. http://dx.doi.org/10.1016/j.ajpe.2024.100962.

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