Modeling the Player

Gamification ◽  
2015 ◽  
pp. 668-682
Author(s):  
Johannes Konert ◽  
Michael Gutjahr ◽  
Stefan Göbel ◽  
Ralf Steinmetz
Keyword(s):  
Learning Styles ◽  
Personality Traits ◽  
Learning Style ◽  
Social Connectedness ◽  
Short Version ◽  
Game Based Learning ◽  
Learning Style Inventory ◽  
Efficiency And Effectiveness ◽  
Profile Characteristics ◽  
Style Preferences

For adaptation and personalization of game play sophisticated player models and learner models are used in game-based learning environments. Thus, the game flow can be optimized to increase efficiency and effectiveness of gaming and learning in parallel. In the field of gaming still the Bartle model is commonly used due to its simplicity and good mapping to game scenarios, for learning the Learning Style Inventory from Kolb or Index of Learning Styles by Felder and Silverman are well known. For personality traits the NEO-FFI (Big5) model is widely accepted. When designing games, it is always a challenge to assess one player's profile characteristics properly in all three models (player/learner/personality). To reduce the effort and amount of dimensions and questionnaires a player might have to fill out, we proved the hypothesis that both, Learning Style Inventory and Bartle Player Types could be predicted by knowing the personality traits based on NEO-FFI. Thus we investigated the statistical correlations among the models by collecting answers to the questionnaires of Bartle Test, Kolb LSI 3.1 and BFI-K (short version of NEO-FFI). A study was conducted in spring 2012 with six school classes of grade 9 (12-14 year old students) in two different secondary schools in Germany. 74 students participated in the study which was offered optionally after the use of a game-based learning tool for peer learning. We present the results statistics and correlations among the models as well as the interdependencies with the student's level of proficiency and their social connectedness. In conclusion, the evaluation (correlation and regression analyses) proved the independency of the models and the validity of the dimensions. Still, especially for all of the playing style preferences of Bartle's model significant correlations with some of the analyzed other questionnaire items could be found. As no predictions of learning style preferences is possible on the basis of this studies data, the final recommendation for the development of game-based learning application concludes that separate modeling for the adaptation game flow (playing) and learn flow (learning) is still necessary.

Modeling the Player

2014 ◽  
Vol 4 (2) ◽  
pp. 36-50 ◽  
Author(s):  
Johannes Konert ◽  
Michael Gutjahr ◽  
Stefan Göbel ◽  
Ralf Steinmetz
Keyword(s):  
Learning Styles ◽  
Personality Traits ◽  
Learning Style ◽  
Social Connectedness ◽  
Short Version ◽  
Game Based Learning ◽  
Learning Style Inventory ◽  
Statistical Correlations ◽  
Profile Characteristics ◽  
Style Preferences

For adaptation and personalization of game play sophisticated player models and learner models are used in game-based learning environments. Thus, the game flow can be optimized to increase efficiency and effectiveness of gaming and learning in parallel. In the field of gaming still the Bartle model is commonly used due to its simplicity and good mapping to game scenarios, for learning the Learning Style Inventory from Kolb or Index of Learning Styles by Felder and Silverman are well known. For personality traits the NEO-FFI (Big5) model is widely accepted. When designing games, it is always a challenge to assess one player's profile characteristics properly in all three models (player/learner/personality). To reduce the effort and amount of dimensions and questionnaires a player might have to fill out, we proved the hypothesis that both, Learning Style Inventory and Bartle Player Types could be predicted by knowing the personality traits based on NEO-FFI. Thus we investigated the statistical correlations among the models by collecting answers to the questionnaires of Bartle Test, Kolb LSI 3.1 and BFI-K (short version of NEO-FFI). A study was conducted in spring 2012 with six school classes of grade 9 (12-14 year old students) in two different secondary schools in Germany. 74 students participated in the study which was offered optionally after the use of a game-based learning tool for peer learning. We present the results statistics and correlations among the models as well as the interdependencies with the student's level of proficiency and their social connectedness. In conclusion, the evaluation (correlation and regression analyses) proved the independency of the models and the validity of the dimensions. Still, especially for all of the playing style preferences of Bartle's model significant correlations with some of the analyzed other questionnaire items could be found. As no predictions of learning style preferences is possible on the basis of this studies data, the final recommendation for the development of game-based learning application concludes that separate modeling for the adaptation game flow (playing) and learn flow (learning) is still necessary.

scholarly journals Student Profiling as a Tool for Inclusive Instructional Design: A Case of a 3rd Year Biotechnology Class, University of Namibia

2021 ◽  
Vol 4 (4) ◽  
pp. p12
Author(s):  
Timothy Sibanda ◽  
Nchindo R. Mbukusa ◽  
Ezekiel G. Kwembeya
Keyword(s):  
Instructional Design ◽  
Learning Styles ◽  
Personality Traits ◽  
Instructional Strategies ◽  
Learning Style ◽  
Learning Preferences ◽  
The Other ◽  
Home Setting ◽  
Learning Style Preferences ◽  
Style Preferences

Massification of Higher Education (HE) has made it difficult for teachers to design instructional strategies that are responsive to the diverse student needs. We here argue that student profiling is a handy tool that the HE teacher can use for inclusive instructional design by thoughtfully selecting learning and teaching strategies, and materials and supports that will maximise student achievement. We designed a student-profiling instrument focusing on capturing students’ biographical information, learning preferences, anticipated learning outcomes, personality traits, and learning related skills-set and administered to students in a 3rd Year Biotechnology class at the University of Namibia. The data on learning style preferences was analysed using the VARK Questionnaire (version 8.01) while a Chi-square (?2) test of association (SPSS software version 24) was used to determine whether there was a relationship between students’ preferred learning styles and the other variables. Seventy-five percent (75%) of the students had multimodal learning preferences while 25% were unimodal for kinesthetic learning style. No students preferred visual or auditory learning alone. The ?2 test revealed no significant relationship between students’ preferred learning styles and any of the other variables including age, place of origin, home language, home setting, residence during school semester, pre-course anticipation, skills set, and personality traits (P > 0.05). We conclude that profiling students’ learning preferences prior to teaching and learning helps HE teachers to tailor their instructional strategies to students’ learning style preferences, maximises epistemological access, as well as enhance inclusivity, equality and equity.

scholarly journals Learning Styles of Undergraduate Medical Students

2018 ◽  
Vol 59 (2) ◽  
Author(s):  
Michelle Cortés Barré ◽  
Javier Francisco Gullén Olaya
Keyword(s):  
Medical Students ◽  
Learning Styles ◽  
Learning Style ◽  
First Year ◽  
Undergraduate Medical Students ◽  
Effective Learning ◽  
Learning Style Inventory ◽  
Learning Style Preferences ◽  
Style Preferences ◽  
First Year Medical Students

<strong>Introduction: </strong>According to the experiential learning theory, each person develops a learning style that characterizes his/her preferred way to acquire and transform experiences to create knowledge. The objective of this study was to identify the learning styles of undergraduate medical students. <strong>Methods: </strong>The Kolb Learning Style Inventory was applied to first-year medical students at the Pontificia Universidad Javeriana (Bogotá, Colombia) during the second period of 2009. <strong>Results: </strong>204 students completed the questionnaire (the average age was 18.5 years; 55% were women). Students preferred the abstract styles of learning, including assimilating (47%) and converging (27%) styles. <strong>Conclusions: </strong>Having information about medical students learning style preferences can help educators to design teaching strategies that promote a more effective learning. Teachers should provide a variety of learning contexts to stimulate the strengthening of their abilities.

scholarly journals The construction and evaluation of a normative learning style preference questionnaire

2001 ◽  
Vol 27 (3) ◽  
Author(s):  
M. J. Viljoen ◽  
J. M. Schepers ◽  
K. Van Zyl
Keyword(s):  
Factor Analysis ◽  
Learning Styles ◽  
Learning Style ◽  
Focal Point ◽  
Learning Style Inventory ◽  
Learning Style Preferences ◽  
The Matrix ◽  
Style Preferences ◽  
Learning Style Preference ◽  
Direct Oblimin

Various authors have indicated the need for and value of identifying the learning style preferences of individual learners. Similar needs have been voiced in the South African context.The focal point of this study was the development of a normative instrument for predicting the preferred learning styles of individuals. Secondary aims were to determine whether there are differences between groups formed on the basis of gender, academic qualifications and functional disciplines as far as their learning style preferences are concerned. Based on a review of the literature and an existing questionnaire, namely the Learning Style Inventory (LSI 85), the Learning Style Preference Questionnaire (LSPQ) consisting of 136 items was developed and administered to respondents (N= 542) in a large organisation. The LSPQ was subjected to a principal factor analysis and six factors were obtained.The six factors were rotated to simple structure by means of the Direct Oblimin procedure. The matrix of intercorrelations of the six factorswas subjected to a second-order factor analysis and yielded a single factor. Opsomming Verskeie outeurs het na die behoefte aan asook die waarde van identi¢kasie van leerstylvoorkeure van individuele leerders verwys. Soortgelyke behoeftes is ook in Suid-Afrikaanse verband geopper.Die fokus van hierdie studie was die ontwikkeling van ’n normatiewe instrument om die leerstylvoorkeure van individue te meet. Sekondere doelwitte was omte bepaal of daar verskille tussen groepe is wat saamgestel is op grond van geslag, akademiese kwalifikasies en funksionele dissiplines wat hul leerstylvoorkeure betref. Gegrond op ’n oorsig van die literatuur en ’n bestaande vraelys, tewete die ‘‘Learning Style Inventory’’ (LSI 85), is die ‘‘Learning Style PreferenceQuestionnaire‘‘ (LSPQ), bestaande uit 136 items, gekonstrueer en op 542 respondente in’n groot organisasie toegepas. Die LSPQ is aan ’n hoo¡aktorontleding onderwerp en ses faktore is verkry. Die ses faktore is deur middel van die Direct Oblimin-prosedure na eenvoudige struktuur geroteer.

scholarly journals Profiling sports therapy students' preferred learning styles within a clinical education context

2015 ◽  
Author(s):  
Christopher Holland ◽  
Claire D Mills
Keyword(s):  
Clinical Practice ◽  
Learning Styles ◽  
Learning Style ◽  
Clinical Education ◽  
Group Analysis ◽  
Gender Comparison ◽  
Learning Style Inventory ◽  
Practice Experience ◽  
Significant Difference ◽  
Style Preferences

The aim of this study was to report the learning style preferences of final year Sports Therapy students within the context of clinical education, with a further specific focus on differences between male and female learning styles. A total of n = 32 BSc. (Hons) Sports Therapy degree students ( x̄ ± s; age = 21.8 ± 4.8 years, male:female = 14:18) were recruited from the University of Gloucestershire whilst completing a 24 week clinical practice module. Data collection involved the Kolb learning style inventory (version 3.1) being administered to all participants with reference to their clinical practice experience. Data analysis, involving mean scores for these learning style orientations, were then used to determine the group preference for abstractness over concreteness (AC-CE) and action over reflection (AE-RO). Group analysis revealed a preference for the converging learning style (AC-CE = 5.3, AE-RO = 5.2) and was in contrast to the favoured individual learning styles of Accommodator (34%) and Diverger (31%). These individual findings are consistent with Kolb & Kolb’s (2005) belief that individuals involved in human-related professions are person orientated and likely to adopt concrete learning styles. Gender comparison revealed a statistically significant difference between the AC-CE scores (P = 0.03), possibly leading to the assumption that male Sports Therapy students have a predilection for more abstract modes of experiential learning (8.6), whereas females have a slight preference for more concrete means (2.7), suggesting a more balanced learning style. The findings of this study indicate that learning activities could be tailored in order to optimise potential learning within a clinical Sports Therapy context.

Learning Style Preferences of Undergraduate Nursing Students: A Systematic Review

2019 ◽  
Vol 21 (1) ◽  
Author(s):  
Tonderai Washington Shumba ◽  
Scholastika Ndatinda Iipinge
Keyword(s):  
Systematic Review ◽  
Academic Performance ◽  
Academic Success ◽  
Nursing Students ◽  
Learning Styles ◽  
Learning Style ◽  
Undergraduate Nursing Students ◽  
Learning Style Preferences ◽  
Undergraduate Nursing ◽  
Style Preferences

This study sought to synthesise evidence from published literature on the various learning style preferences of undergraduate nursing students and to determine the extent they can play in promoting academic success in nursing education of Namibia. A comprehensive literature search was conducted on electronic databases as a part of the systematic review. Although, kinaesthetic, visual and auditory learning styles were found to be the most dominant learning style preferences, most studies (nine) indicated that undergraduate nursing students have varied learning styles. Studies investigating associations of certain demographic variables with the learning preferences indicated no significant association. On the other hand, three studies investigating association between learning styles and academic performance found a significant association. Three studies concluded that indeed learning styles change over time and with academic levels. The more nurse educators in Namibia are aware of their learning styles and those of their students, the greater the potential for increased academic performance.

Comparison of Learning Styles between Physical Education and Dance Majors

1984 ◽  
Vol 58 (2) ◽  
pp. 583-588 ◽  
Author(s):  
Dorothy B. Zakrajsek ◽  
Rebecca L. Johnson ◽  
Diane B. Walker
Keyword(s):  
Physical Education ◽  
Learning Styles ◽  
Learning Style ◽  
T Test ◽  
Education Majors ◽  
Learning Style Inventory ◽  
Physical Education Majors

Learning styles of dance and physical education majors were described and compared. Subjects were 167 declared majors in 1982 from 9 universities (87 PE, 80 dance; 44 males, 115 females). Kolb's Learning Style Inventory which measures abstractness or concreteness and activity or reflectivity was given. By t test (.05) no significant differences in preferred learning style were found between majors or genders.

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