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i-manager's Journal on Educational Psychology (JPSY)

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Methods for Enhancing Memory Performance in a Type of Learning (Forgetting) of Categorized Mind States
Exploring Need for Enhancing Play Activity Time in School Settings for Holistic Development of Learners
A Survey Study on the Status of Life Skills of Secondary Students of Dakshina Kannada District
Effectiveness of Outdoor Teaching Activities on Basic Science Process Skills of Secondary School Students
Impact on Trainees Growth and Challenges during the Internship in B.Ed. Course
The Impact of the Lecture Approach on Students' Attitudes towards Chemistry: A Comparative Study of Overall, Cognitive, Affective, and Behavioral Dimensions

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Volume 11 Issue 1 May - July 2017

Article

Psychometric Studies: Review on Theories of Intelligence and Achievement

David R. Squires*

Assistant Professor, Instructional Design & Educational Technology, Texas A&M University, Corpus Christi, USA

Squires, D.R. (2017). Psychometric Studies: Review on Theories of Intelligence and Achievement. i-manager’s Journal on Educational Psychology, 11(1),1-4. https://doi.org/10.26634/jpsy.11.1.13646

Abstract

There are a multitude of different theories on intelligence and achievement. While intelligence theory remains a highly contentious issue, there are commonalties among prominent research based and non-research based theories, particularly the adoption of belief over testable theory by researchers. The embracing of speculative theory exemplifies a serious dilemma when combining multiple theories to create an archetypal definition. Conjecture can often take the place of measureable analysis. Shedding light on a single pinnacle theory of intelligence remains conjectural, due to the highly complex and nuanced nature of human development. Furthermore, there are immeasurably different perspectives on the meaning of intelligence, and the implications of intelligence theory in general. However, exhaustive research based theories often produce the greatest impact when tested effectively and placed within the context of investigative evaluation. This paper seeks to examine the various components of intelligence theory in order to develop a more comprehensive approach that identifies how intelligence is a complex combination of many different factors.

References

[1]. Campitelli, G., & Gobet, F. (2011). Deliberate Practice: Necessary but not sufficient. Current Directions in Psychological Science. 20(5), 280-285.

[2]. Ericsson, K. A., Nandagopal, K., & Roring, R. W. (2005). Giftedness viewed from the expert-performance perspective. Journal for the Education of the Gifted, 28(3), 287-311.

[3]. Greven, C. U., Harlaar, N., Kovas, Y., Chamorro- Premuzie, & Plomin, R. (2009). More than just IQ: School achievement is predicted by self-perceived abilities- but for genetic rather than environmental reasons. Psychological Science, 20(6), 753-762.

[4]. Lichtenstein, P., & Pedersen, N. L. (1997). Does genetic variance for cognitive abilities account for genetic variance in educational achievement and occupational status? A study of twins reared apart and twins reared together. Social Biology, 44(1-2), 77-90.

[5]. Loehlin, J. C, Horn J. M., & Willerman, L. (1994). Differential inheritance of mental abilities in the Texas Adoption Project. Intelligence. 19(3), 325–336.

[6]. Plomin, R. & Asbury, K. (2005). Nature and Nurture: Genetic and Environmental Influences on Behavior. Annals of the American Academy of Political and Social Science, 600(1), 86-98.

[7]. Reynolds, C. A., Finkel, D., McArdle, J. J., Gatz, M., Berg, S., Pedersen, N. (2005). Quantitative genetic analysis of latent growth curve models of cognitive abilities in adulthood. Dev Psychol., 41(1), 3–16.

[8]. Schneider, W. (1993). Acquiring expertise: Determinants of exceptional performance. In K. A. Heller, F. J. Monks & A. H. Passow (Eds.), International Handbook of Research and Development of Giftedness and Talent (pp. 311-324). Oxford: Pergamon Press.

[9]. Tudge, J. R. H., Hogan, D. M., Snezhkova, I. A., Kulakova, N. N., & Etz, K. E. (2000). Parents' child-rearing values and belief in the United States and Russia: The impact of culture and social class. Infant and Child Development, 9(2), 105-121.

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Research Paper

The Relation between Resilience and Life Satisfaction in Pre-Service PreschoolTeachers in Turkey

Gï¿½?nselI Yildirim* , Sibel SÌ¦nmez**

* Associate Professor, Department of Preschool Education, Faculty of Education, Dokuz Eylul University, Izmir, Turkey

** Assistant Professor, Department of Preschool Education, Faculty of Education, Ege University, Izmir, Turkey

Yildirim,G., and Sönmez, S. (2017). The Relation between Resilience and Life Satisfaction in Pre-Service Preschool Teachers in Turkey. i-manager’s Journal on Educational Psychology, 11(1), 5-13. https://doi.org/10.26634/jpsy.11.1.13647

Abstract

At present, it is important that individuals have wellness and abilities to cope with problems and to create solutions to problems. These abilities influence individuals' life satisfaction and resilience levels. Life satisfaction refers to well-being and predominance of positive feelings over negative feelings. It is agreed that the less the discrepancy between desires and achievements is, the higher the life satisfaction is. Resilience and life satisfaction are two concepts which have gained importance recently. The objective of this study was to examine factors influencing resilience and life satisfaction and the relation between resilience and life satisfaction in pre-service preschool teachers at Dokuz Eylül University and Ege University. The study was based on the relational screening model. Data were collected with the Resilience Scale and the Satisfaction with Life Scale in the spring term of the 2015/2016 academic year. Two hundred students were included into the study through random sampling. Of 200 students, 181 (90.5%) were female and 19 (9.5%) were male. Data were analyzed with independent samples t test, one-way variance analysis, and Pearson correlation analysis. Resilience and its several subscales are associated with life satisfaction. As resilience increases so does life satisfaction. Social support is effective in improvement of resilience. Young people living in metropolises are lucky in terms of gaining leadership features and being full of life. In addition, young people feeling happy with their study field can be more powerful and full of life and have more initiative and goals. The students luckiest in terms of being optimistic and full of life can be the ones having middle socio-economic status. The positive relation between resilience and life satisfaction reveals the significance of resilience. Therefore, children should be provided with appropriate environments which will develop resilience. Besides, families and teachers should be informed about the issue. Awareness of the society about social support, which helps develop resilience, could also be increased and importance of support from peers, families and relatives in lives of individuals could be emphasized. In addition, suitable environments could be provided for social activities at and outside school.

References

[1]. Abolghasemi, A. & Varaniyab, S. T. (2010). Resilience and perceived stress: Predictors of life satisfaction in the students of success and failure. Procedia Social and Behavioral Sciences, 5, 748?752.

[2]. Achour, M. & Nor, M. (2014). The Effects of Social Support and Resilience on Life Satisfaction of Secondary School Students, Journal of Academic and Applied Studies, 4(1), 12-20.

[3]. Arli, M. & Nazik, M. H (2001). Bilimsel Arastirmaya Giris. Gazi kitabevi, Ankara

[4]. Bonanno, G.A. (2004). Loss, trauma, and human resilience: Have we underestimated the human capacity to thrive after extremely aversive events? American Psychologist, 59, 20–28.

[5]. Borman, G. D., & Rachuba, L. T. (2001). Academic success among poor and minority students (Report No. 52). Washington, DC: Center for Research on the Education of Students Placed at Risk

[6]. Brown, W. K. & Rhodes, W. A. (1991). Factors that Promote Invulnerability and Resiliency in at-risk Children. In W. A. Rhodes & W. K. Brown (Eds.), Why Some Children Succeed Despite the Odd (171-177). USA: Praeger.

[7]. Cohn, M. A., Fredrickson, B. L., Brown, S. L. Mikels, J. A., & Conway, A. M. (2009). Happiness unpacked: Positive emotions increase life satisfaction by building resilience, Emotion, 9 (3), 361-368.

[8]. Diener, E. D., Emmons, R. A., Larsen, R. J., & Griffin, S. (1985). The Satisfaction with Life Scale. Journal of Personality Assessment, 49, 71-75.

[9]. Diener, E., Oishi, S., & Lucas, R. E. (2003). Personality, culture, and subjective wellbeing: Emotional and cognitive evaluations of life. Annu. Rev. Psychol., 54, 403- 425.

[10]. Fredrickson, B. L., Cohn, M. A., Coffey, K. A., Pek, J., & Finkel, S.M. (2008). Open hearts build lives: Positive emotions, induced through loving-kindness meditation, build consequential personal resources. Journal of Personality and Social Psychology, 95 (5), 1045?1062.

[11]. Frisch, M. B. (2006). Quality of Life Therapy: Applying a Life Satisfaction Approach to Positive Psychology and Cognitive Therapy. New Jersey: John Wiley & Sons

[12]. Greenberg, J. S. (2011). Comprehensive Stress th Management (12 Edition). New York: McGraw-Hill.

[13]. Green, D., Oswald, M., & Spears, B. (2007). Teachers' (mis)understanding of resilience. International Education Journal, 8:133-144.

[14]. Güloglu, B. & Karairmak, Ö. (2010). Self-esteem and resilience as the predictors of loneliness among university students. Journal of Ege Education,2 (11), 73–88.

[15]. Gürgan, U. (2006). Yilmazlik ölçegi (YÖ): Ölçek gelistirme, güvenirlik ve geçerlik çalismasi. Ankara Üniversitesi Egitim Bilimleri Fakültesi Dergisi, 39(2), 45-74

[16]. Huebner, E. S., Drane, J. W., & Valois, R. F. (2000). Levels and demographic correlates of adolescent life satisfaction reports. School Psychology International, 21, 281-292.

[17]. Karasar, N. (1999). Bilimsel Arastirma Yöntemi. Nobel Yayinevi, Ankara.

[18]. Kobasa, S. C. (1979). Stressful Life Events, Personality and Health: An Inquiry into Hardiness. Journal of Personality and Social Psychology, 37, 1-11.

[19]. LeFalle, D. (2010). The role of personal strengths in academic success: Views and voices of resilient community college students (Unpublished doctoral dissertation, California Institute of Integral Studies, San Francisco, CA).

[20]. Liu, Y., Wang, Z., & Lü, W. (2013). Resilience and affect balance as mediators between trait emotional intelligence and life satisfaction. Personality and Individual Differences, 54, 850-855.

[21]. Mahanta, D., & Aggarwal, M. (2013). Effect of Perceived Social Support on Life Satisfaction of University students. European Academic Research, 1(6), 1083- 1094.

[22]. Masten, A. S. (2001). Ordinary magic: Resilience processes in development. American Psychologist, 56, 227–238.

[23]. Milstein, M. M., & Henry, A. D. (2008). Leadership for resilient schools and communities. Corwin Pres, CA.

[24]. Mojdegan, S., Moghidi, F., & Ahghar, Q. (2013). Study of the relationship between happiness and selfefficacy with self-resilience of preschool teachers in Tehran. Applied Scientific Reports, 2(1), 10-16.

[25]. Myers, D. G. & Diener, E. (1995). “Who Is Happy?” Psychological Science, 6, 10-19

[26]. Naftali, A. & Vella-Brodrick, D. A. (2008). Studying happiness: Wellbeing interventions and individual t h differences. Proceedings of the 10 Australian Conference on Quality of Life, Deakin University.

[27]. Norrish, J. & Vella-Brodrick, D. A. (2008). Is the study of happiness a worthy scientific pursuit? Social Indicators Research, 87, 393-407.

[28]. Özbey, S., Büyüktanir, A., & Türkoglu, D. (2014). An Investigation of Preservice Pre-School Teachers Resilience Skills. Procedia-Social and Behavioral Sciences, 116, 4040–4046.

[29]. Peterson, C. Park, N., & Seligman, M. (2005). Orientations to happiness and life satisfaction: The full life versus the empty life. Journal of Happiness Studies, 6, 25- 41.

[30]. Sirgy, J. M. & Wu, J. (2007). The pleasant life, the engaged life, and the meaningful life: What about the balanced life. Journal of Happiness Studies, DOI 10.1007/s10902-007-9074-1.

[31]. Utsey, S. O, Hook, J. N, Fischer, N., & Belvet, B. (2008). Cultural orientation, ego resilience, and optimism as predictors of subjective well-being in African Americans. The Journal of Positive Psychology, 3, 202-210.

[32]. Werner, E., & Smith, R. (1992). Overcoming the odds: High risk children from birth to adulthood. New York: Cornell University Press.

[33]. Yetim Ü. (1991). Kisisel Projelerin Organizasyonu ve Örüntüsü Açisindan Yasam Doyumu. (Doktora Tezi, Ege Üniversitesi, Izmir).

[34].Yildirim, Y., Kirimoglu, H., & Temiz, A. (2010). A Research on resiliency of physical education and sports teachers that work in primary and secondary education schools (example of Hatay province). Beden Egitimi ve Spor Bilimleri Dergisi, 4(1), 88-97.

[35]. Youngblom, R, Houlihan, D & Nolan, J. (2014). An Assessment of Resiliency and Life Satisfaction in High School-Aged Students in Belize. International Journal of Psychological Studies, 6(4), 115-122.

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Research Paper

Rapport, Perceptions of Effectiveness, and Course Grade Expectations, ACorrelational Analysis

Erin Yezbick* , Jeremy I. Tutty**

* Communications Instructor, Baker College of Flint, USA.

** Dissertation Chair, University of Phoenix, and Senior Instructional Design Analyst, Rio Salado College, Tempe, USA.

Yezbick ,E., and Tutty,J.I. (2017). Rapport, Perceptions of Effectiveness, and Course Grade Expectations, A Correlational Analysis. i-manager’s Journal on Educational Psychology, 11(1), 14-25. https://doi.org/10.26634/jpsy.11.1.13645

Abstract

The purpose of this study was to determine whether a relationship exists between student/instructor rapport, student perceptions of instructor effectiveness, and course grade expectations. Previous studies have determined that rapport affects motivation (Bergström, 2010; Frisby, Berger, Burchett, Herovic, & Strawser, 2014; Legg & Wilson, 2009), perceptions of teacher effectiveness (Giles, 2011; Kozub, 2010), and evaluation scores (Barth, 2008; Kowai-Bell, Guadango, Little, & Ballew, 2012). Student ratings of instruction are the most widely used measure of college teaching effectiveness. Determining what causes one subject to boost a student's rapport with the instructor might help educators apply that knowledge to other subjects. The study was conducted as quantitative research using a non-experimental correlational research design. Data were collected using two instruments, the Professor-Student Rapport Scale and the IDEA Student Ratings of Instruction Short Form. The data were analyzed using Pearson product-moment correlation coefficient (Pearson's r) and Spearman's rank-order correlation coefficient (Spearman's r_s ). The study found statistically significant positive correlations between Professor-Student Rapport and Instructor Evaluation and between Professor-Student Rapport and Student Expected Course Grade.

References

[1]. Awang, H., & Ismail, N. A. (2010). Undergraduate education: A gap analysis of students' expectations and st satisfaction. Problems of Education in the 21 Century, 21(1), 21-28.

[2]. Barth, M. M. (2008). Deciphering student evaluations of teaching: A factor analysis approach. Journal of Education for Business, (84)1, 40-46.

[3]. Bates, E. A., & Kaye, L. K. (2014). ''I'd be expecting caviar in lectures'': The impact of the new fee regime on undergraduate students' expectations of higher education. Higher Education, 67(5), 656-673. doi: 10.1007/s10734-013-9671-3

[4]. Benton, S. L., Li, D., Gross, A., Pallett, W. H., & Webster, R. J. (2013). Transactional distance and student ratings in online college courses. American Journal of Distance Education, 27(4), 207-217. doi: 10.1080/08923647.2013. 838458

[5]. Bergström, P. (2010). Process-based assessment for professional learning in higher education: Perspectives on the student-teacher relationship. International Review of Research in Open and Distance Learning, 11(2), 33-48.

[6]. Bryant, D. (2014). Expectations of student learning quality. Australian Universities' Review, 56(1), 32-38.

[7]. Chan, P. E., Graham-Day, K. J., Ressa, V. A., Peters, M. T., & Konrad, M. (2014). Beyond involvement: Promoting student ownership of learning in classrooms. Intervention in School and Clinic, 50(2), 105-113.

[8]. Chickering, A.W. (2006). Every student can learn-If… About Campus, 11(2), 9-15. doi:10.1002/ abc.161

[9]. Cohen, J. (1988). Statistical Power Analysis for the nd Behavioral Sciences, 2 ed. New York: Routledge Academic. ISBN-13: 978-0805802832

[10]. Del Guercio, R. (2011). Back to the Basics of Classroom Management. Education Digest: Essential Readings Condensed for Quick Review, 76(5), 39-43.

[11]. Delucchi, M. (2000). Don't worry, be happy: Instructor likability, student perceptions of learning, and teacher ratings in upper-level sociology courses. Teaching Sociology, 28(3), 220-231.

[12]. Drouin, M., & Vartanian, L. R. (2010). Students' feelings of and desire for sense of community in face-toface and online courses. The Quarterly Review of Distance Education, 11(3), 147-159.

[13]. Ellsworth, J. A. (1993). Teaching/learning relationship. Education, 114(2), 307-318.

[14]. Estepp, C. M., & Roberts, T. G. (2013). Exploring the relationship between professor/student rapport and students' expectancy for success and values/goals in college of agriculture classrooms. Journal of Agricultural Education, 54(4), 180-194. doi:10.5032/jae.2013.04180

[15]. Freiberg, H. J., & Lamb, S. M. (2009). Dimensions of person-centered classroom management. Theory into Practice, 48(2), 99-105.

[16]. Frisby, B. N., Berger, E., Burchett, M., Herovic, E., & Strawser, M. G. (2014). Participation apprehensive students: The influence of face support and instructor–student rapport on classroom participation. Communication Education, 63(2), 105-123. doi:10.1080/03634523.2014.881516

[17]. Frisby, B. N., & Martin, M. M. (2010). Instructor-student and student-student rapport in the classroom. Communication Education, 59(2), 146-164.

[18]. Frisby, B. N., & Myers, S. A. (2008). The relationships among perceived instructor rapport, student participation, and student learning outcomes. Texas Speech Communication Journal, (33)1, 27-34.

[19]. Gabriel, M. A., Campbell, B., Wiebe, S., MacDonald, R. J., & McAuley, A. (2012). The role of digital technologies in learning: Expectations of first year university students. Canadian Journal of Learning and Technology, 38(1), 1-18.

[20]. Gall, M. D., Gall, J. P., & Borg, W. R. (2007). Education th Research: An Introduction (8 ed.).Boston, MA: Pearson.

[21]. Garces-Ozanne, A., & Sullivan, T. (2014). Expectations and reality: What you want is not always what you get. Australian Journal of Adult Learning, 54(2), 78- 100.

[22]. Giles, D. (2011). Relationships always matter: Findings from a phenomenological research inquiry. Australian Journal of Teacher Education, 36(6), 80-91.

[23]. Glover, J. I. (2012). Finding the right mix: Teaching methods as predictors for student progress on learning objectives (Doctoral Dissertation). Retrieved from ProQuest (3513644).

[24]. Green, S., & Salkind, N. (2003). Using SPSS for Windows and Macintosh: Analyzing and Understanding rd Data (3 ed.). Upper Saddle River, NJ: Prentice Hall.

[25]. Greenfield, S. (2011). Podcasting: A new tool for student retention? Journal of Nursing Education, 50(2), 112-114. doi:10.3928/01484834-20101230-06

[26]. Gruber, T., Reppel, A., & Voss, R. (2010). Understanding the characteristics of effective professors: The student's perspective. Journal of Marketing for Higher Education, 20(2), 175-190. doi:10.1080/08841241.2010. 526356

[27]. Heckert, T. M., Latier, A., Ringwald, A., & Silvey, B. (2006). Relation of course, instructor, and student characteristics to dimensions of student ratings of teaching effectiveness. College Student Journal, 40(1), 195-203.

[28]. Howell, D. C. (2011). Fundamental Statistics for the th Behavioral Sciences (7 ed.). Belmont, CA: Wadsworth Cengage Learning.

[29]. IDEA Education (2002). Short form – Student reactions to instruction and courses. Retrieved from http://ideaedu.org/sites/default/files/Student_Ratings_Dia gnostic_Form.pdf

[30]. Ilgaz, H., & Gülbahar, Y. (2015). A snapshot of online learners: E-Readiness, e-satisfaction, and expectations. International Review of Research in Open and Distributed Learning, 16(2), 171-187.

[31]. Kowai-Bell, N., Guadagno, R. E., Little, T. E., & Ballew, J. L. (2012). Professors are people too: The impact of informal evaluations of professors on students and professors. Social Psychology of Education, 15(3), 337- 351. doi:10.1007/s11218-012-9181-7

[32]. Kozub, R. M. (2010). Relationship of course, instructor, and student characteristics to dimensions of student ratings of teaching effectiveness in business schools. American Journal of Business Education, (3)1, 33-40.

[33]. Legg, A. M., & Wilson, J. H. (2009). E-mail from professor enhances student motivation and attitudes. Teaching of Psychology, (36)3, 205-211. doi:10.1080/ 00986280902960034

[34]. Malouff, J. M., & Hall, L. (2012). The Value of Meeting Individually with Students Early in a Term. Online Submission.

[35]. Mearns, J. (2009). Social learning theory. In H. Reis & S. Sprecher (eds.), Encyclopedia of Human Relationships (Vol. 3, pp. 1537-1540). Thousand Oaks, CA: Sage.

[36]. Murphy, E., & Rodriguez-Manzanares, M. A. (2012). Rapport in distance education. International Review of Research in Open and Distance Learning, 13(1), 167-190.

[37]. O'Neill, S., & Thomson, M. M. (2013). Supporting academic persistence in low-skilled adult learners. Support for Learning, 28(4), 162-172. doi:10.1111/1457-9504.12038

[38]. O'Toole, S. & Essex, B. (2012). The adult learner may really be a neglected species. Australian Journal of Adult Learning, 52(1), 183-191.

[39]. Pittenger, A., & Doering, A. (2010). Influence of motivational design on completion rates in online selfstudy pharmacy-content courses. Distance Education, 31(3), 275-293. doi:10.1080/01587919.2010.513953

[40]. Rogers, D. T. (2015). Further validation of the learning alliance inventory: The roles of working alliance, rapport, and immediacy in student learning. Teaching of Psychology, 42(1), 19-25. doi:10.1177/ 009862831456 2673

[41]. Ryan, R. G., Wilson, J. H., & Pugh, J. L. (2011). Psychometric characteristics of the professor-student rapport scale. Teaching of Psychology, 38(3), 135-141. doi:10.1177/0098628311411894

[42]. Starcher, K. (2011). Intentionally building rapport with students. College Teaching, 59(4), 162. doi:10.1080/87 567555.2010.516782

[43]. Wilson, J. H., & Ryan, R. G. (2013). Professor-student rapport scale: Six items predict student outcomes. Teaching of Psychology, 40(2), 130-133. doi:10.1177/009 8628312475033

[44]. Wilson, J. H., Ryan, R. G., & Pugh, J. L. (2010). Professor-student rapportscale predicts student outcomes. Teaching of Psychology, 37(4), 246-251. doi:10.1080/00986283.2010.510976

[45]. Young, L. E., Horan, S. M., & Frisby, B. N. (2013). Fair and square? An examination of classroom justice and relational teaching messages. Communication Education, 62(4), 333-351. doi:10.1080/03634523.2013. 800216

[46]. Zhou, J. (2012). The effects of reciprocal imitation on teacher–student relationships and student learning outcomes. Mind, Brain, & Education, 6(2), 66-73. doi:10.1111/j.1751-228X.2012.01140.x

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Research Paper

Tri–Assessment Analysis: An Innovative Model for Inquiry and Confirmatory DataAnalysis via the Novel Tri–Mentoring Model Designed to Measure MentoringEfficacy

James Edward Osler II*

Faculty Member, North Carolina Central University, USA.

Osler, J. E., II. (2017). Tri–Assessment Analysis: An Innovative Model for Inquiry and Confirmatory Data Analysis via the Novel Tri–Mentoring Model Designed to Measure Mentoring Efficacy. i-manager’s Journal on Educational Psychology, 11(1), 26-39. https://doi.org/10.26634/jpsy.11.1.13650

Abstract

The aim of this paper is to provide a faculty model for positive mentoring was first explored at an African American Historically Black College and University [or “HBCU”]. The purpose of this paper is to present the mentoring model and an analogous trichotomous data analysis methodology referred to as “Tri–Assessment” that is used to determine the validity of the mentoring experience. The research methodology of the mentoring model measures positive mentoring outcomes and is applicable for measuring mentoring as a whole. The model has its foundations in trichotomy drawing upon the research work of the author who has established the field of “Triostatistics” (Osler, 2014), trichotomous research design (Osler, 2012), and the arena of trichotomous psychometric measurement (Osler, 2013a). This paper is organized into various sections that highlight mentoring history, mentoring at an HBCU, and mentoring measurement through the presented model. The example presented of the “Tri–Mentoring Model” presented has the following results: 1.) Identification of positive mentoring traits and characteristics; 2.) An in-depth and accurate way of measuring the outcomes of any mentoring process (as authentically delivered by the participant experiencing the actual mentoring); and lastly 3.) The categorization of positive mentoring outcomes by using the example of faculty mentoring that took place at a HBCU. The author further recommends that both the “Tri–Mentoring Model” and the “Tri–Assessment” research methodology have the unlimited potential to open new arenas of inquiry and data analysis in the diverse field of mentoring and beyond.

References

[1]. American Speech-Language-Hearing Association (2007a). ASHA 2006 Member Counts. Retrieved March 19, 2007, from http://www.asha.org/about/membershipcertification/ member-data/member-counts.htm

[2]. American Speech-Language-Hearing Association (2007b). S.T.E.P. 1:1 – Student to Empowered Professional Mentoring Program. Retrieved March 19, 2007, from http://www.asha.org/students/gatheringplace/step/

[3]. Anderson, J. (1988). The education of Blacks in the South, 1860-1935. Chapel Hill: University of North Carolina Press.

[4]. Brown, M. C., & Davis, J. E. (2001). The historically black college as social contract, social capital, and social equalizer. Peabody Journal of Education, 76(1), 31- 49.

[5]. Brown, M. C., Donahoo, S., & Bertrand, R. D. (2001). The black college and the quest for educational opportunity. Urban Education, 36(5), 533-571.

[6]. Drewry, H. N., & Doermann, H. (2004). Stand and prosper: Private Black college and their students. Princeton: Princeton University Press.

[7]. Kemp, B. J. (2005). Ancient Egypt: Anatomy of a civilisation. Boca Raton, FL: Routledge.

[8]. National Academy of Sciences, National Academy of Engineering, Institute of Medicine. (1997). Adviser, teacher, role model, friend: On being a mentor to students in science and engineering. Washington, DC: The National Academies Press.

[9]. Oakes, L., & Gahlin, L. (2003). Ancient Egypt. New York: Barnesand Noble Books.

[10]. Osler II, J.E. (2012). Introducing: Trichotomy– Squared – A Novel Mixed Methods Test and Research Procedure Designed to Analyze, Transform, and Compare Qualitative and Quantitative Data for Education Scientists Who are Administrators, Practitioners, Teachers, and Technologists. i-manager's Journal on Mathematics, 1(3), 23-32.

[11]. Osler II, J.E. (2013a). The Psychometrics of Educational Science: Designing Trichotomous Inventive Investigative Instruments for Qualitative and Quantitative Inquiry. i-manager's Journal on School Educational Technology, 8(3),15-22.

[12]. Osler II, J.E. (2013b). The Psychological Efficacy of Education as a Science through Personal, Professional, and Contextual Inquiry of the Affective Learning Domain. i-manager's Journal on Educational Psychology, 6(4), 36-41.

[13]. Osler, J. E. (2014). Triostatistics: The Application of Innovative In–Depth Advanced Post Hoc Statistical Metrics for the Assessment and Analysis of Statistically Significant Tri–Squared Test Outcomes. Kentucky Journal of Excellence in College Teaching and Learning, 12(3), 27–39.

[14]. Outcalt, C. L., & Skewes-Cox, T. E. (2002). Involvement, interaction and satisfaction: The human environment at HBCUs. The Review of Higher Education, 25(3), 331-347.

[15]. Palmer, R., & Gasman, M. (2008). “It takes a village to raise a child”: The role of social capital in promoting academic success for African American men at a Black college. Journal of College Student Development, 49(1), 52-70. Retrieved from http://management.about.com/ cs/people/a/mentoring.htm

[16]. Reh, F. J. (2007). Mentors and mentoring: What is a mentor. About. com: Management.

[17]. Roberts, A. (1999). The origins of the term mentor. History of Education Society Bulletin, 64, 313–329.

[18]. Rust, J., & Golombok, S. (1989). Modern Psychometrics: The Science of Psychological Assessment nd (2 ed.). Florence, KY, US: Taylor & Frances/Routledge

[19]. Sensagent. (2012). Sensagent Corporation: Retrieved, May 9, 2012 from http://dictionar y. sensagent.com/ trichotomy+(mathematics)/en-en/

[20]. Singh, S. (1997). Fermat's enigma: The epic quest to solve the world's greatest mathematical problem. A. Books a Division of Random House. New York, NY

[21]. Teo, T. (2005). The Critique of Psychology: From Kant to Postcolonial Theor y. New York, NY: Springer Science+Business Media, Inc.

[22]. Thomas, K. M. (2005). Diversity Dynamics in the Workplace. Wadsworth Publishing Company

[23]. Thomas, K. M., Willis, L. A., & Davis, J. (2007). Mentoring minority graduate students: Issues and strategies for institutions, faculty, and students. Equal Opportunities International, 26(3), 178-192.

[24]. Torrance, E. P. (1984). Mentor Relationships: How they Aid Creative Achievement, endure, change, and die. Bearly, Limited.

[25]. U.S. Department of Education (2008). HBCUs: A National Resource. White House Initiative on Historically Black Colleges and Universities.

[26]. Vance, C. (2002). Mentoring at the edge of chaos. Creative Nursing, 8(3), 7.

[27]. Wilde, B. J., & Garrett, S. C. (1991). Mentoring in graduate schools of education: Mentees' perceptions. The Journal of Experimental Education, 59(2), 165-179.

[28]. Wright-Harp, W., & Cole, P. A. (2008). A mentoring model for enhancing success in graduate education. Contemporary Issues in Communication Science and Disorders, 35, 4-16.

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Research Paper

How Does Mind Processes Information and Represents Knowledge: An EmpiricalStudy

Ananta Kumar Jena* , Bhujendranath Panda**

* Assistant Professor, Department of Education, Assam University, Silchar, India.

** Professor & Head, Department of Education, Regional Institute of Education (NCERT), Bhubaneswar, India

Jena, A.K., and Panda,B. (2017). How Does Mind Processes Information and Represents Knowledge: An Empirical Study. i-manager’s Journal on Educational Psychology, 11(1), 40-52. https://doi.org/10.26634/jpsy.11.1.13652

Abstract

The study aimed to know how does mind-map software assess the representation of learners' knowledge and how brain tester software assess the performance of left, right, auditory, and visual lobes of the brain to represent information. It also aimed to study the differential effectiveness of audio, visual, and audio-visual information to represent knowledge. Mind map tool used to know the students' knowledge representation in science, and for that purpose, different audio, visual, and audio-visual tools used to know how learners process cognitive information; those were experienced in the study. There was no hypothesis to draw inferences but three working hypotheses or the research questions framed to find out the result. Every individual has an independent information processor in left, right, auditory, and visual lobe of brain to represent information. It was also resulted that audio-visual information was more effective to process and represent knowledge than audio and visual information.

References

[1]. Bechtereva, N. P., Gogolitsin, Y. L., Ilyukhina, V. A., Pakhomov, S. V. (1983). Dynamic neurophysiological correlates of mental processes. International Journal of Psychophysiology,1 (1), 49-63.

[2]. Boudelaa, S. & Marslen-Wilson, W. D. (2004). Allomorphic variation in Arabic: Implications for lexical processing and representation. Brain and Language, 90(1–3), 106-116.

[3]. Brüne, M. & Brüne-Cohrs, U. (2006). Theory of mind evolution, ontogeny, brain mechanisms a n d psychopathology. Neuroscience & Biobehavioral Reviews, 30(4), 437-455.

[4]. Burr, J. E. & Hofer, B. K. (2002). Personal epistemology and theory of mind: Deciphering young children's beliefs about knowledge and knowing. New Ideas in Psychology, 20 (2–3), 199-224.

[5]. Caron, A. J. (2009). Comprehension of the representational mind in infancy. Developmental Review, 29(2), 69-95.

[6]. Chaudhary, S. (1998). Knowledge of language and the multilingual mind. Language Sciences, 20(2), 201- 220.

[7]. De Villiers, J. (2007). The interface of language and Theory of Mind. Lingua, 117(11), 1858-1878.

[8]. Dove, G. (2009). Beyond perceptual symbols: A call for representational pluralism. Cognition, 110(3), 412- 414.

[9]. Esfahani, L. & Kellett, J. (1988). Integrated graphical approach to knowledge representation and acquisition. Knowledge-Based Systems, 1(5), 301-309.

[10]. Fekete, T. & Edelman, S. (2011). Towards a computational theory of experience. Consciousness and Cognition, 20(3), 807-827.

[11]. Fingelkurts, A. A., Fingelkurts, A. A., Neves, C. F. H. (2013). Consciousness as a phenomenon in the operational architectonics of brain organization: Criticality and self-organization considerations. Chaos, Solitons & Fractals, 55, 13-31.

[12]. Flavell, J. H., Green, F. L., Flavell, E. R. (1990). Developmental changes in young children's knowledge about the mind. Cognitive Development, 5(1), 1-27.

[13]. Gallese, V. & Goldman, A. (1998). Mirror neurons and the simulation theory of mind-reading. Trends in Cognitive Sciences, 2(12), 493-501.

[14]. Gallistel, C. R. (2011). Current developments in cognitive psychology, neuroscience, and the philosophy of mind. Advances in Psychology, 138, 2006, 5-22.

[15]. Harvey, J. G. & Harris, D. D. (1996). Enhancing the blackboard concept to produce a flexible, extensible knowledge-based design tool. Knowledge-Based Systems, 9(4), 233-243.

[16]. Hedberg, P. H.& Higgins, E. T. (2011). What remains on your mind after you are done?: Flexible regulation of knowledge accessibility. Journal of Experimental Social Psychology, 47(5), 882-890.

[17]. Hsu, J. S., Liang, T. P., Wu, S. P. J., Klein, G., Jiang, J. J. (2011). Promoting the integration of users and developers to achieve a collective mind through the screening of information system projects. International Journal of Project Management, 29(5), 514-524.

[18]. Khrennikov, A. (2004). Probabilistic pathway representation of cognitive information. Journal of Theoretical Biology, 231(4), 597-613.

[19]. Khrennikov, A. (2011). Quantum-like model of processing of information in the brain based on classical electromagnetic field. Biosystems, 105(3), 250-262.

[20]. Kiefer, M. & Pulvermüller, F. (2012). Conceptual representations in mind and brain: Theoretical developments, current evidence and future directions. Cortex, 48(7), 805-825.

[21]. Knauff, M. (2006). A neuro-cognitive theory of relational reasoning with mental models and visual images. Advances in Psychology, 138, 127-152.

[22]. Laskey, K. B. (2008). MEBN: A language for first-order Bayesian knowledge bases. Artificial Intelligence, 172(2–3), 140-178.

[23]. Lesgold, A. (1993). Beyond A Commodity View of Knowledge in Instruction. Advances in Psychology, 101, 425-433.

[24]. Mainzer, K. (2009). From embodied mind to embodied robotics: Humanities and system theoretical aspects. Journal of Physiology-Paris, 103(3–5), 296-304.

[25]. Maton, K. (2013). Making semantic waves: A key to cumulative knowledge-building. Linguistics and Education, 24(1), 8-22.

[26]. McGeer, V. & Pettit, P. (2002). The self-regulating mind. Language & Communication, 22(3), 281-299.

[27]. McNamara, T.P. (1986). Mental representations of spatial relations. Cognitive Psychology, 18(1), 87-121.

[28]. Merchie, E. & Van Keer, H. (2012). Spontaneous Mind Map Use and Learning from Texts: The Role of Instruction and Student Characteristics. Procedia - Social and Behavioral Sciences, 69, 1387-1394.

[29]. Obersteiner, A., Reiss, K., Ufer, S. (2013). How training on exact or approximate mental representations of number can enhance first-grade students' basic number processing and arithmetic skills. Learning and Instruction, 23, 125-135.

[30]. O'Brien, G. & Opie, J .(2004). Chapter 1 - Notes Toward a Structuralist Theory of Mental Representation. Representation in Mind: New Approaches to Mental Representation, 1-20.

[31]. Oztop, E., Wolpert, D., Kawato, M. (2005). Mental state inference using visual control parameters. Cognitive Brain Research, 22(2), 129-151.

[32]. Papaxanthis, C., Pozzo, T., Skoura, X., Schieppati, M. (2002). Does order and timing in performance of imagined and actual movements affect the motor imagery process? The duration of walking and writing task. Behavioural Brain Research, 134(1–2), 209-215.

[33]. Peled, A. (2005). Plasticity imbalance in mental disorders the neuroscience of psychiatry: Implications for diagnosis and research. Medical Hypotheses, 65(5), 947- 952.

[34]. Pulvermuller, F. & Mohr, B. (1996). The Concept of Transcortical Cell Assemblies: a Key to the Understanding of Cortical Lateralization and Interhemispheric Interaction. Neuroscience & Biobehavioral Reviews, 20(4), 557-566.

[35]. Purzycki, B. G. (2013). The minds of gods: A comparative study of supernatural agency. Cognition, 129(1), 163-179.

[36]. Rakhlin, N., Kornilov, S. A., Reich, J., Babyonyshev, M., Koposov, R. A.,Grigorenko, E. L. (2011). The relationship between syntactic development and Theory of Mind: Evidence from a small-population study of a developmental language disorder. Journal of Neurolinguistics, 24(4), 476-496.

[37]. Rauhut, H. & Lorenz, J. (2011). The wisdom of crowds in one mind: How individuals can simulate the knowledge of diverse societies to reach better decisions. Journal of Mathematical Psychology, 55(2), 191-197.

[38]. Sauvage, C., Jissendi, P., Seignan, S., Manto, M., Habas, C. (2013). Brain areas involved in the control of speed during a motor sequence of the foot: Real movement versus mental imager y. Journal of Neuroradiology, In Press, Corrected Proof, Available online 21 February 2013.

[39]. Stevens, J. A. (2005). Interference effects demonstrate distinct roles for visual and motor imagery during the mental representation of human action. Cognition, 95(3), 329-350.

i-manager's Journal on Educational Psychology (JPSY)

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Volume 11 Issue 1 May - July 2017

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Gï¿½?nselI Yildirim* , Sibel SÌ¦nmez**

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Rapport, Perceptions of Effectiveness, and Course Grade Expectations, ACorrelational Analysis

Erin Yezbick* , Jeremy I. Tutty**

* Communications Instructor, Baker College of Flint, USA. ** Dissertation Chair, University of Phoenix, and Senior Instructional Design Analyst, Rio Salado College, Tempe, USA.

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Tri–Assessment Analysis: An Innovative Model for Inquiry and Confirmatory DataAnalysis via the Novel Tri–Mentoring Model Designed to Measure MentoringEfficacy

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How Does Mind Processes Information and Represents Knowledge: An EmpiricalStudy

Ananta Kumar Jena* , Bhujendranath Panda**

* Assistant Professor, Department of Education, Assam University, Silchar, India. ** Professor & Head, Department of Education, Regional Institute of Education (NCERT), Bhubaneswar, India

Jena, A.K., and Panda,B. (2017). How Does Mind Processes Information and Represents Knowledge: An Empirical Study. i-manager’s Journal on Educational Psychology, 11(1), 40-52. https://doi.org/10.26634/jpsy.11.1.13652

Abstract

References

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* Associate Professor, Department of Preschool Education, Faculty of Education, Dokuz Eylul University, Izmir, Turkey

** Assistant Professor, Department of Preschool Education, Faculty of Education, Ege University, Izmir, Turkey

* Communications Instructor, Baker College of Flint, USA.

** Dissertation Chair, University of Phoenix, and Senior Instructional Design Analyst, Rio Salado College, Tempe, USA.

* Assistant Professor, Department of Education, Assam University, Silchar, India.

** Professor & Head, Department of Education, Regional Institute of Education (NCERT), Bhubaneswar, India