Myers-Briggs Research Articles

A Review on Personalization of Gamified Learning Environments*

This study explores the personalization of gamification in educational contexts, particularly adaptive approaches to meet diverse learner needs. The study examines terminologies and offer definitions for adaptive, tailored, personalized, and customized gamification. Personalization serves as an umbrella term covering any changes in the process. Customization is the changes performed by the user/learner; tailored gamification involves adjustments made at the beginning and adaptive gamification involves system-driven changes as things progress. The analysis of adaptive gamification studies is structured around adaptation criteria, adaptation process, adaptation data, and adaptive intervention. Adaptation criteria includes player types, personality models, learning styles, and hybrid profiles. Adaptation process includes user-controlled and system-controlled adaptation. User-controlled adaptation refers to customization; system-controlled adaptation is examined under static adaptation, dynamic adaptation, and combination of these two. Adaptation data is categorized under explicit and implicit information collection. Lastly, recommendations, and adjusting game elements and mechanics are discussed under adaptation intervention. The review highlights the commonly used player typologies, including Bartle, Hexad, and BrainHex, and personality models such as Big Five and Myers-Briggs Type Indicator. The review identifies limitations in current frameworks, stressing the importance of standardized models and guidelines to implement adaptive gamification and incorporating gamification analytics to sustain adaptation and automation.

The Relationship between the Myers-Briggs Type Indicator (MBTI) Types and Psychological Well-being among College Students in China

Aim: This study explores the relationship between Myers-Briggs Type Indicator (MBTI) personality types and psychological well-being among Chinese college students, examining how cultural factors influence this relationship and identifying key factors impacting students' mental health. Methodology: A systematic literature review was conducted, focusing on peer-reviewed articles from the past decade. Databases such as PubMed, PsycINFO, and Google Scholar were searched using keywords like "MBTI," "psychological well-being," "college students," and "China." Inclusion criteria included studies on MBTI and psychological well-being among Chinese college students. Results: The review found that 64% of extraverted students reported high life satisfaction, compared to 42% of introverted students. Sensing students showed 58% academic satisfaction, while only 45% of intuitive students reported similar satisfaction levels. Thinkers (60%) and feelers (55%) displayed high psychological well-being linked to their respective environments. Judging types reported 70% life satisfaction, whereas only 45% of perceiving types expressed similar satisfaction. These findings underscore the significant impact of MBTI personality types on the psychological well-being of Chinese college students. Conclusion: MBTI types significantly influence psychological well-being among Chinese college students, moderated by cultural, social, and educational factors. Tailored mental health interventions and supportive environments are essential to address the diverse needs of students. Recommendations: Colleges should integrate MBTI-based counseling services, provide flexible learning options, and promote social support networks. These measures will accommodate varying personality types and improve overall student well-being. Implications: Understanding the interplay between MBTI types and psychological well-being within the Chinese cultural context offers valuable insights for educators and mental health professionals. These insights can inform the development of culturally sensitive interventions and support systems, enhancing the mental health and academic success of college students.

The Relationships between the Myers-Briggs Type Indicator (MBTI), Job satisfaction and Well-being among Working College Students in China

The phenomenon of working college students is on the rise in China. Evidence elsewhere suggests that working while studying can be problematic for students' well-being. This research sought to assess whether personality types and job satisfaction can be used to prevent the decline of well-being among working college students in the country. It specifically examined the effects of Myers-Briggs Type Indicator (MBTI) types on job satisfaction and well-being, relationship between job satisfaction and well-being wellbeing, and the moderating roles of field of study and emotional state in these relationships. Based on the findings, these objectives have been successfully met. The findings show that MBTI personality types significantly shape both job satisfaction and well-being. Scoring highly on Extraversion, Sensing, Thinking, and Judging predicts high job satisfaction and better well-being among the students. Job satisfaction was also found to positively impact well-being for working students. Additionally, the findings also show that the field of study and emotional state moderate the stated relationships. The findings of this study are sound as they generally align with what other researchers have established. The findings imply that Myers-Briggs Type Indicator (MBTI) types and job satisfaction can be applied and targeted to enhance the well-being of working college students in China as the phenomenon continues to grow.

Fluid Modernity and Virtual Communities: An Analysis of the Popularity of MBTI on Social Media

This paper, rooted in Zygmunt Baumans theory of modernity, examines the formation of virtual communities and the characteristics of liquid modernity as manifested in the widespread phenomenon of Myers-Briggs Type Indicator (MBTI) on social media. As a psychological assessment tool, MBTI has pervaded social media platforms, engendering virtual communities characterized by high fluidity and consumerist tendencies. Through participatory observation and online ethnography, this study delves into the MBTI virtual communities on the "Xiaohongshu" platform, exploring their consumerism-driven formation mechanisms and cultural attributes. In modern society, virtual communities exhibit dynamic stability and structural elasticity, with identity constantly being reshaped and redefined within these virtual spaces. The popularity of MBTI underscores the anxieties surrounding identity in contemporary society and reflects the liquid nature of modern identity formation. Under the influence of technology and consumerism, virtual communities have emerged as a significant social form in modern society.

Personality in motion: How intuition and sensing personality traits relate to lower limb rebound performance.

Embodied cognition asserts a symbiotic relationship between cognitive processes and the physical body, raising an intriguing question: could personality traits be intertwined with the biomechanical performance of the lower limb? This study aimed to explore this connection by examining how personality traits, assessed using the Myers-Briggs Type Indicator (MBTI), relate to lower limb rebound power (RP) measured through the five-repetition rebound jump test. Eighty participants completed two sessions: a biomechanical analysis of hopping using an Optojump® system to measure contact time, flight time, and RP, and a personality traits assessment categorizing traits across four MBTI axes: extraversion-introversion (favorite world); sensing-intuition (information processing preference); thinking-feeling (decision making); and judging-perceiving (structure). Participant characteristics did not significantly differ across MBTI axes (p≥0.07), minimizing potential confounding factors. Notably, individuals classified as intuitive showed significantly longer flight times (p = 0.02) and larger RP (p = 0.007) compared to sensing individuals, suggesting a greater reliance on the fast stretch-shortening cycle and showcasing superior use of their lower limb structures as springs. This suggests potential implications for sports performance, with intuition individuals possibly excelling in plyometric sports. However, no significant associations were found between biomechanical performance and the other three MBTI axes (p≥0.12), challenging the initial hypothesis. This research provides initial insights into the nuanced relationship between personality traits and movement patterns, indicating the potential for tailored physical interventions to enhance adherence and optimize responses in training programs.

Personality and emotion—A comprehensive analysis using contextual text embeddings

Personality and emotions have always been closely intertwined since humans evolved, adapting to these two forms. Emotions are indicative of a person’s personality, and vice versa. This paper aims to investigate the complex relationship between these two fundamental aspects of human behavior using the concepts of machine learning and statistical analysis. The objective is to automate the process of determining the relationship between personality traits of the MBTI (Myers-Briggs Type Indicator) and Ekman’s emotions based on the context of user-written social media posts using contextual embedding. A robust mechanism is employed, involving two main phases to figure out emotions from the social media posts. The first phase involves determining the cosine similarity scores between each MBTI personality trait and predefined emotions. The second phase introduces a cross-dataset learning approach where several machine learning models are trained on a dataset labeled with emotions to learn patterns of emotions found in the text. After training, these models utilize the patterns they learned to predict emotions in a targeted dataset. With an overall accuracy of 85.23%, the Support Vector Machine (SVM) is chosen as the most effective and high-performing model for emotion prediction tasks. We employed a vetting mechanism combining two approaches to improve accuracy, reliability, and trustworthiness for the final emotion prediction. Finally, using statistical quantification, this paper finds patterns that link each MBTI personality trait with Ekman emotions. It reveals that extroverts (E), sensing (S), and feeling (F) personality types are more likely to share joyful and surprising emotional posts, while individuals with extroversion (E), intuition (N), thinking (T), and perception (P) traits tend to express negative emotions such as anger and disgust. Conversely, introverts (I), intuitive (N), thinking (T), and judging (J) personalities are more inclined to share posts reflecting fear and sadness. This comprehensive study provides valuable insights on how individuals with different personality types typically express emotions on social media.

Smart Hostel Allocation System Using Naïve Bayes Algorithm

This research explores the potential of automated personality classification using supervised machine learning techniques, with a specific focus on the Myers-Briggs Type Indicator (MBTI) for hostel allocation. The problem is the manual and resource-intensive allocation of hostel accommodations in educational institutions, leading to personality mismatches among roommates, which negatively impacts students' academic engagement and well-being. The aim of this research is to improve hostel room allocation by predicting student personality traits, thus minimizing personality mismatches among roommates. A Naïve Bayes classifier was applied to the MBTI personality dataset acquired from Kaggle. Various preprocessing techniques, such as tokenization, stop-word removal, and word stemming, were used to prepare the dataset for feature selection. CountVectorizer and TF-IDF methods were employed to convert text into numerical vectors for machine learning analysis. Additionally, SMOTE was implemented to address class imbalance within the dataset, ensuring better model performance. The Naïve Bayes classifier showed promising results, with scores achieved across all personality traits as 73% precision, 70% accuracy, F1 Score 70% and Recall 70% in predicting MBTI personality traits from input text. Visualizations and performance metrics such as accuracy, precision, recall, and F1-score were used to evaluate the model's efficiency. The research findings suggest that supervised machine learning techniques can effectively predict personality traits from social media data, aiding in improved hostel room allocation and potentially benefiting broader applications in education and computational psychology. This system is recommended for educational institutions and residential complexes seeking efficient roommate pairing.

From personality types to social labels: the impact of using MBTI on social anxiety among Chinese youth.

As the Myers-Briggs Type Indicator (MBTI) gains popularity among Chinese young people, it has undergone a gradual transition from being perceived as a personality assessment tool to being regarded as a social label. The objective of this study was to ascertain whether the use of the MBTI as a social label has an impact on social anxiety among Chinese youth groups. A questionnaire survey was conducted on social media platforms to recruit Chinese youth aged 18 to 35. A total of 247 males and 222 females participated in the study, and the data was analyzed quantitatively using SPSS software and the Process macro plugin. The study found no strong correlation between MBTI as a social label and social anxiety. Moreover, this study introduced ego identity, belonging, and impression management as mediating variables and found that, under the influence of ego identity and impression management, the use of MBTI has a significant impact on social anxiety. The research reveals the complex role of MBTI among Chinese youth and provides a new perspective for understanding the impact of online social labels on the mental health of youth groups. Of course, this study also has limitations in terms of sample size and variable control. Future research should expand the sample size, introduce more potential influencing factors, and further validate and expand the existing conclusions.

Enhancing MBTI Personality Prediction from Text Data with Advance Word Embedding Technique.

Understanding human personality traits is crucial for various domains, including psychology, education, and human resources. The Myers-Briggs Type Indicator (MBTI) is a widely recognized psychological assessment tool, categorizing individuals into one of sixteen distinct personality types. The existing methodologies, which primarily relied on Word2Vec embeddings and traditional machine learning models, showed promise but left room for improvement. To address this problem, this research focused on enhancing Myers-Briggs Type Indicator (MBTI) personality prediction from text data through advanced word-embedding techniques, specifically GloVe and BERT. The research investigates the effectiveness of various Machine Learning Classifiers, including Random Forest, XGBoost, LinearSVC, SGD, Logistic Regression, and CatBoost, in predicting MBTI personality types. Additionally, the impact of preprocessing techniques such as text cleaning, tokenization, TF-IDF vectorization, GloVe, and BERT embeddings on classification performance is examined. Furthermore, the research explores strategies for addressing class imbalance through upsampling techniques. Results indicate high accuracy and performance across multiple classifiers, with XGBoost achieving the highest accuracy of 97.33%. The analysis of MBTI dimensions reveals nuanced insights into the classifiers' ability to capture specific personality traits.

Enhancing Production Quality by Avoiding Dishonest Behavior

Purpose: This paper elucidates the determinants of dishonest behavior affecting various domains and aims to demonstrate how addressing these practices can substantially improve overall quality. Methodology/Approach: A framed laboratory experiment with economics students from the University of West Bohemia was conducted, where participants chose between honest and lower-quality production. Using the Holt-Laury method, we measured risk aversion and personality traits using the Myers-Briggs Type Indicator (MBTI). Findings: Increased inspection probability significantly reduced lower-quality production, with a statistical significance level of less than 1%. Thinking type of personality and Risk Aversion are significant at the 10% level, indicating a moderate impact. Conversely, punishment and rewards were statistically insignificant, with p-values exceeding 10%. Research Limitation/Implication: The study is limited by its homogeneous sample of economics students from a single university and insufficient gender representation, which may affect generalizability. Originality/Value of paper: This research provides insights into how inspection probabilities, rewards, punishments, risk aversion, and personal characteristics influence dishonest behavior, aiding the development of strategies to reduce dishonesty and improve overall quality.

Dental students' Myers-Briggs Type Indicator personality profile in the past 50 years: Systematic review and meta-analysis.

Dental students' personalities are strongly correlated with their didactic and clinical performances. With the significant changes in the social environment in the past decades, students' personalities may also change dramatically. Additionally, with the increasing number of international students admitted into US dental programs, educators must pay attention to the potential personality differences between domestic and international students. A systematic review focusing on the Myers-Briggs Type Indicator personality types of dental students was conducted with 11 literature databases following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guideline. The quality assessment of each included article was conducted following the Joanna Briggs Institute Prevalence Critical Appraisal Tool. Meta-analyses were conducted for each personality type within the United States in the past 50 years, and in each country in the past 20 years. Eighteen articles (17 reports) were included after the eligibility assessment. The longitudinal trends within the United States showed the predominant two personality types have changed from Extraversion, Sensing, Feeling, and Judging (ESFJ) and Extraversion, Sensing, Thinking, and Judging (ESTJ) to ESTJ and Introversion, Sensing, Thinking, and Judging (ISTJ) during the past 50 years. When comparing different countries, the United States, China, Korea, and Iran have the same two dominant personality types (ESTJ and ISTJ) but not the Philippines (Extraversion, Intuition, Feeling, and Perceiving and Introversion, Intuition, Feeling, and Perceiving). However, there are large variations in the prevalence of other personality types. There have been constant changes in the predominant personalities of dental students over the years. Additionally, understanding the diversity of personality types within the United States as well as among different countries could serve as the foundation for further improvements in teaching strategies and student support services.

Relationship between Extroversion Personality and Learning Strategy-based on MBTI Test

This study explores the relationship between extroversion personality traits, as measured by the Myers-Briggs Type Indicator (MBTI) test, and learning strategy preferences among English language learners. Employing a quantitative methodology, data were collected from a sample of 1621 participants to investigate the predominant extroversion personality traits and differences in learning strategy selection. The research background emphasizes the significance of understanding individual differences in personality traits and their impact on learning behaviors. The study aims to discern whether extroverted individuals exhibit distinct preferences for specific learning strategies, particularly in metacognition, cognition, compensation, affect, and social interaction. By elucidating these relationships, educators can tailor instructional approaches better to accommodate learners’ diverse needs and strengths, ultimately enhancing educational outcomes.

Self Organizing Maps (SOM) and statistical methods for describing the physicological profile of undergraduates students of engineering

To meet a Brazilian guideline for engineering courses, which advocates the use of active learning in applied disciplines, this research studies new students entering in the Metallurgical Engineering Course in Escola Politécnica of Universidade de São Paulo (PMT/USP). It was applied to them a traditional MTBI (Myers–Briggs Type Indicator) questionary with the aim of finding out if there is recurrence of psychological profiles and to understand the characteristics of the freshmen to learning. This information was subjected to statistical analysis to observe the recurrence of the psychological characteristics of freshmen over the years (2017 to 2021). The data was also subjected to the Self Organizing Maps (SOM) machine learning technique, to delineate and group the psychological profiles observed in the students, enabling the analysis of the psychological characteristics and the comparison with the results obtained via statistics. After that, the results from the MBTI Traditional and the SOM clustering were submitted to comparison methods through multivariate statistics and Multiple Correspondence Analysis (MCA). It was found that there is recurrence of psychological characteristics between the years of collection, what were the psychological profiles of these freshmen as to how they learned. It was found that the freshmen surveyed mostly belong to Generation Z (or iGen) and characteristics pertinent to this group were observed. A scenario is obtained to point out the best active learning techniques for these students with the verification of recurrence of profiles and other correlated psychological characteristics, aiming to provide the most effective teaching in the engineering course.

Logical Thinking in Idealist and Rational Students

The purpose of this study is to describe students’ logical thinking based on Keirsey’s personality types, specifically the Idealist and Rational types, within the topic of social arithmetic. The research adopts a descriptive qualitative approach. Data collection involves three techniques: MBTI (Myers-Briggs Type Indicator) surveys, logical thinking written tests, and semi-structured interviews. The study participants consist of students from classes VII A, VII B, and VII C at SMP Muhammadiyah 9 Watukebo. The research subjects include four students: two with Idealist personality types and two with Rational personality types according to Keirsey’s classification. The findings indicate that none of the research subjects fully meet the three logical thinking indicators, which are grouped into six points. However, there is one indicator that all subjects were able to achieve: the first indicator related to coherence of logical thinking (point B), which involves expressing the general steps used in problem-solving. On the other hand, there are indicators that none of the research subjects were able to fulfill completely. These include the second indicator concerning argumentation ability (point A), which involves articulating the logical reasons for using general steps in problem-solving, and point C, which pertains to expressing the logical reasons behind the correct final answer. Among the research subjects, the subject who successfully fulfills the good logical thinking indicator is the second subject with a rational personality type according to Keirsey’s classification.

The Impact of Project Managers Traits on Project Success

Project management is an indispensable aspect of business that depends heavily on the capabilities and characteristics of the project managers, with his/her personality traits playing an essential role in leading their project to its goals. This paper explores the critical role of the project manager's personality traits and cultural background in the success of project management and emphasizes its influence on team dynamics, stakeholder engagement, and overall project environments. The Big Five personality traits provide a framework for understanding these influences. The paper also delves into how the Myers-Briggs Type Indicator (MBTI) impacts project management approaches, specifically the Extraversion/Introversion and Judgment/Perception dimensions. In addition, the paper examines the impact of global and cultural differences on project manager traits and management styles, emphasizing the need for project managers to adapt to different cultural contexts in a world where understanding and leveraging cultural differences is critical to project success and the achievement of broader strategic goals. This comprehensive analysis offers insights into the multidimensional role of project managers within today's highly dynamic global project management environment.

A Study on MBTI Perceptions in South Korea: Big Data Analysis from the Perspective of Applying MBTI to Contribute to the Sustainable Growth of Communities

This study aimed to assess the potential contributions of the Myers–Briggs Type Indicator (MBTI) to the sustainable growth of communities by conducting a comprehensive analysis of social perceptions of the MBTI in South Korea through big data analysis. The investigation encompasses three primary stages: data collection, preprocessing, and analysis, involving text mining, network analysis, CONCOR analysis, and sentiment analysis. A total of 31,308 text data pieces (13.73 MB) from various sources, including news, blogs, and other sections of Naver and Google, over the past three years, were collected and analyzed using the keyword “MBTI”. Tools, such as Textom SV, UCINET, and NetDraw, were employed for data collection and analysis. The study’s key findings include the identification, through term frequency (TF) and TF-inverse document frequency analyses, of top-ranking terms, such as 16Types, 4Indicators, Test, Myself, OthersMBTI, Situation, and Contents. The CONCOR analysis further revealed six clusters, encompassing themes like interest in MBTI personality tests, application of 16 types in daily life, MZ’s MBTI consumption patterns, trending of MBTI characters, extension to K-Test, and professional use of MBTI. Moreover, sentiment analysis indicated that 68.5% of individuals in South Korea expressed a positive sentiment towards MBTI, while 31.5% conveyed a negative sentiment. The specific emotions identified included liking (Good Feeling), disgust, and interest, in order of prominence. In light of these findings, this study delineates a spectrum of perceptions regarding MBTI in South Korea, encompassing both positive interests and negative concerns. To ensure the responsible use of MBTI, it is imperative to implement reliable scientific testing and education, mitigate the potential harm of stereotyping, and reshape social perceptions surrounding MBTI usage. Only through these measures can MBTI genuinely contribute to the sustainable growth of communities without being confined to limiting stereotypes.

Frequency and Comparison of Personality Types of Pre-Medical and First-Year Medical Students in Choosing Medicine as a Career Choice and its Association with the Education System and Socioeconomic Status

Frequency and Comparison of Personality Types of Pre-Medical and First-Year Medical Students in Choosing Medicine as a Career Choice and its Association with the Education System and Socioeconomic Status

Factors influencing willingness to use MBTI social applications in youth groups - based on a technology acceptance model

The Myers-Briggs Type Indicator (MBTI) was developed from Carl Gustav Jung’s theory of personality classification and designated by American psychologists as a personality test indicator that classifies people into sixteen different personality attributes and assigns different identities to each of the sixteen personalities. Today, the MBTI is one of the most widely used instruments in the world to measure normal personality differences, and is widely used in employment, education, and social occasions. A large-scale group discussion has been formed on the Internet, and through the fluctuation of the Internet, MBTI is taking on a new look and dominating the social discourse of young people as a new social currency. This study explores the youth group as the research object, and digs out the reasons why it has become the social currency, as well as the state of mind of the contemporary youth group and the social willingness of the contemporary youth through the analysis of this new subculture.

Mind to move: Differences in running biomechanics between sensing and intuition shod runners.

Delving into the complexities of embodied cognition unveils the intertwined influence of mind, body, and environment. The connection of physical activity with cognition sparks a hypothesis linking motion and personality traits. Hence, this study explored whether personality traits could be linked to biomechanical variables characterizing running forms. To do so, 80 runners completed three randomized 50-m running-trials at 3.3, 4.2, and 5m/s during which their running biomechanics [ground contact time (tc), flight time (tf), duty factor (DF), step frequency (SF), leg stiffness (kleg), maximal vertical ground reaction force (Fmax), and maximal leg compression of the spring during stance (ΔL)] was evaluated. In addition, participants' personality traits were assessed through the Myers-Briggs Type Indicator (MBTI) test. The MBTI classifies personality traits into one of two possible categories along four axes: extraversion-introversion; sensing-intuition; thinking-feeling; and judging-perceiving. This exploratory study offers compelling evidence that personality traits, specifically sensing and intuition, are associated with distinct running biomechanics. Individuals classified as sensing demonstrated a more grounded running style characterized by prolonged tc, shorter tf, higher DF, and greater ΔL compared to intuition individuals (p≤0.02). Conversely, intuition runners exhibited a more dynamic and elastic running style with a shorter tc and higher kleg than their sensing counterparts (p≤0.02). Post-hoc tests revealed a significant difference in tc between intuition and sensing runners at all speeds (p≤0.02). According to the definition of each category provided by the MBTI, sensing individuals tend to focus on concrete facts and physical realities while intuition individuals emphasize abstract concepts and patterns of information. These results suggest that runners with sensing and intuition personality traits differ in their ability to use their lower limb structures as springs. Intuition runners appeared to rely more in the stretch-shortening cycle to energetically optimize their running style while sensing runners seemed to optimize running economy by promoting more forward progression than vertical oscillations. This study underscores the intriguing interplay between personality traits of individuals and their preferred movement patterns.

The Language Model Can Have the Personality: Joint Learning for Personality Enhanced Language Model (Student Abstract)

With the introduction of large language models, chatbots are becoming more conversational to communicate effectively and capable of handling increasingly complex tasks. To make a chatbot more relatable and engaging, we propose a new language model idea that maps the human-like personality. In this paper, we propose a systematic Personality-Enhanced Language Model (PELM) approach by using a joint learning mechanism of personality classification and language generation tasks. The proposed PELM leverages a dataset of defined personality typology, Myers-Briggs Type Indicator, and produces a Personality-Enhanced Language Model by using a joint learning and cross-teaching structure consisting of a classification and language modelling to incorporate personalities via both distinctive types and textual information. The results show that PELM can generate better personality-based outputs than baseline models.