- -

Quality of Learning Support for Mathematics in Transition to University

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Quality of Learning Support for Mathematics in Transition to University

Mostrar el registro completo del ítem

Pampaka, M.; Hutcheson, G.; Williams, J. (2014). Quality of Learning Support for Mathematics in Transition to University. REDU. Revista de Docencia Universitaria. 12(2):97-118. https://doi.org/10.4995/redu.2014.5642

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/139972

Ficheros en el ítem

Thumbnail
Nombre: Pampaka;Hutcheson ...
Tamaño: 1.739Mb
Formato: PDF
Descripción: Versión editorial
Abrir/Preview

Metadatos del ítem

Título: Quality of Learning Support for Mathematics in Transition to University
Otro titulo: Calidad del apoyo para el aprendizaje de las matemáticas en la transición a la Universidad.
Autor: Pampaka, Maria Hutcheson, Graeme Williams, Julian
Fecha difusión:
Resumen:
[EN] We   report   on   the   development   and validation  of  an  instrument  that measures students’ perceptions of ‘the quality and effectiveness of the learning support’ (for mathematics) during their transition to ...[+]


[ES] Este artículo muestra el desarrollo y la validación de un instrumento de medida de las percepciones de los estudiantes de secundaria acerca de, la calidad y la eficacia del apoyo para el aprendizaje de las matemáticas, ...[+]
Palabras clave: Higher Education , Transition , Mathematics education , STEM , Teaching and learning Quality , Measurement , Rasch model , Educación superior , Transiciones , Educación matemática , Educación científico-tecnológica y matemática , Enseñanza y aprendizaje de calidad , Medida , Modelo de Rasch
Derechos de uso: Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
Fuente:
REDU. Revista de Docencia Universitaria. (issn: 1887-4592 ) (eissn: 1887-4592 )
DOI: 10.4995/redu.2014.5642
Editorial:
Universitat Politècnica de València
Versión del editor: https://doi.org/10.4995/redu.2014.5642
Tipo: Artículo

References

Agresti, A. (1996). An Introduction to Categorical Data Analysis. London: John Wiley & Sons, Inc.

Alcock, L., Attridge, N., Kenny, S., & Inglis, M. (2014). Achievement and behaviour in undergraduate mathematics: personality is a better predictor than gender. Research in Mathematics Education, 16(1), 1-17.

Andrich, D. (1999). Rating Scale Model. In G. N. Masters & J. P. Keeves (Eds.), Advances in Measurement in Educational Research and Assessment (pp. 110 - 121). Oxford: Pergamon. [+]
Agresti, A. (1996). An Introduction to Categorical Data Analysis. London: John Wiley & Sons, Inc.

Alcock, L., Attridge, N., Kenny, S., & Inglis, M. (2014). Achievement and behaviour in undergraduate mathematics: personality is a better predictor than gender. Research in Mathematics Education, 16(1), 1-17.

Andrich, D. (1999). Rating Scale Model. In G. N. Masters & J. P. Keeves (Eds.), Advances in Measurement in Educational Research and Assessment (pp. 110 - 121). Oxford: Pergamon.

Baeten, M., Struyven, K., & Dochy, F. (2013). Student-centred teaching methods: Can they optimise students' approaches to learning in professional higher education? Studies in Educational Evaluation, 39(1), 14-22.

Ball, S., Davies, J., David, M., & Raey, D. (2002). 'Classification' and 'Judgement': social class and the 'cognitive structures' of choice of Higher Education. British Journal of Sociology of Education, 23(1), 51-72.

Bell, N. J., Wieling, E., & Watson, W. (2007). Narrative processes of identity construction: Micro indicators of developmental patterns following transition to university. Identity, 7(1), 1-26.

Biggs, J., Kember, D., & Leung, Y. P. (2001). The revised two-factor Study Process Questionnaire: R-SPQ-2F. British Journal of Educational Psychology, 71, 133-149.

Black, L., Williams, J., Hernandez-Martinez, P., Davis, P., Pampaka, M., & Wake, G. (2010). Developing a 'leading identity': the relationship between students' mathematical identities and their career and higher education aspirations. Educational Studies in Mathematics, 73(1), 55-72.

Boaler, J. (1999). Participation, knowledge and beliefs: A community perspective on mathematics learning. Educational Studies in Mathematics, 40(3), 259-281.

Boaler, J., & Greeno, J. (2000). Identity, Agency and Knowing in Mathematics Worlds. In J. Boaler (Ed.), Multiple Perspectives on Mathematics Teaching and Learning. Westport: Ablex Publishing.

Bodycott, P. (1997). A model for supporting student learning and development at the tertiary level. Innovations in Education and Teaching International, 34(3), 219-225.

Bond, T. G., & Fox, C. M. (2001). Applying the Rasch Model: Fundamental Measurement in the Human Sciences. NJ: Lawrence Erlbaum Associates Inc.

Cassidy, C., & Trew, K. (2004). Identity change in Northern Ireland: A longitudinal study of students' transition to University. Journal of Social Issues, 60(3), 523-540.

Chaisanit, S., Trangansri, A., & Meeanan, L. (2012). The development of online interactive whiteboard for supporting collaboration learning. Research Journal of Applied Sciences, Engineering and Technology, 4(16), 2660-2665.

Chamorro-Premuzic, T., Furnham, A., & Lewis, M. (2007). Personality and approaches to learning predict preference for different teaching methods. Learning and Individual Differences, 17(3), 241-250.

Cook, A., & Leckey, J. (1999). Do Expectations Meet Reality? A survey of changes in first-year student opinion. Journal of Further and Higher Education, 23(2), 157 - 171.

D'Agostino, J. V., & Bonner, S. M. (2009). High School Exit Exam Scores and University Performance. Educational Assessment, 14, 25-37.

Han, H., Nelson, E., & Wetter, N. (2014). Medical students' online learning technology needs. Clinical Teacher, 11(1), 15-19.

Harley, D., Winn, S., Pemberton, S., & Wilcox, P. (2007). Using texting to support students' transition to university. Innovations in Education and Teaching International, 44(3), 229-241.

Harnisch, H., & Taylor-Murison, L. (2012). Transition and technology - Evaluation of blended learning delivered by university staff to 6th form students. British Journal of Educational Technology, 43(3), 398-410.

Heirdsfield, A., Walker, S., & Walsh, K. (2005). Developing peer mentoring support for TAFE students entering 1st -year university early childhood studies. Journal of Early Childhood Teacher Education, 26(4), 423-436.

Hoffman, J. P. (2004). Generalized Linear Models: An Applied Approach: Pearson Education.

Hourigan, M., & O'Donoghue, J. (2007). Mathematical under-preparedness: the influence of the pre-tertiary mathematics experience on students' ability to make a successful transition to tertiary level mathematics courses in Ireland. International Journal of Mathematical Education in Science and Technology, 38(4), 461-476.

Howie, P., & Bagnall, R. (2012). A critique of the deep and surface approaches to learning model. Teaching in Higher Education, 18(4), 389-400.

Hoyles, C., Newman, K., & Noss, R. (2001). Changing patterns of transition from school to university mathematics. International Journal of Mathematical Education in Science and Technology, 32(6), 829-845.

Hutcheson, G., Pampaka, M., & Williams, J. S. (2011). Enrolment, achievement and retention on 'traditional' and 'use of mathematics' AS courses. Research in Mathematics Education, 13(2),147-168.

Hutcheson, G., & Sofroniou, N. (1999). The Multivariate Social Scientist. Introductory Statistics Using Generalized Linear Models. London: Sage.

Jackson, L. M., Pancer, S. M., Pratt, M. W., & Hunsberger, B. E. (2000). Great expectations: The relation between expectancies and adjustment during the transition to university. Journal of Applied Social Psychology, 30(10), 2100-2125.

Karantzas, G. C., Avery, M. R., Macfarlane, S., Mussap, A., Tooley, G., Hazelwood, Z., & Fitness, J. (2013). Enhancing critical analysis and problem-solving skills in undergraduate psychology: An evaluation of a collaborative learning and problem-based learning approach. Australian Journal of Psychology, 65(1), 38-45.

Linacre, J. M. (2002). Optimizing Rating Scale Category Effectiveness Journal of Applied Measurement, 3(1), 85-106.

Linacre, J. M. (2014). Winsteps® Rasch measurement computer program. Beaverton, Oregon: Winsteps.com.

Lopez, W. A. (1996). Communication Validity and Rating Scales. Rasch Measurement Transactions, 10 (1), 482-483.

Lowe, H., & Cook, A. (2003). "Mind the Gap: Are students prepared for higher education?". Journal of Further and Higher Education, 27(1), 53-76.

Loyens, S. M. M., Gijbels, D., Coertjens, L., & Côté, D. J. (2013). Students' approaches to learning in problem-based learning: Taking into account professional behavior in the tutorial groups, self-study time, and different assessment aspects. Studies in Educational Evaluation, 39(1), 23-32.

Messick, S. (1989). Validity. In R. L. Linn (Ed.), Educational Measurement (Third ed., pp. 13-103). USA: American Council of Education and the Oryx Press.

Pampaka, M., Kleanthous, I., Hutcheson, G. D., & Wake, G. (2011). Measuring mathematics self-efficacy as a learning outcome. Research in Mathematics Education, 13(2), 169-190.

Pampaka, M., Pepin, B., & Sikko, S. A. (forthcoming). Supporting or alienating students during their transition to Higher Education: mathematically relevant trajectories in two educational contexts. International Journal of Educational Research (Special Issue, on Alienation from Mathematics)

Pampaka, M., Williams, J., & Hutchenson, G. (2012). Measuring students' transition into university and its association with learning outcomes. British Educational Research Journal, 38(6), 1041-1071.

Pampaka, M., & Williams, J. S. (2010). Measuring Mathematics Self Efficacy of students at the beginning of their Higher Education Studies. Paper presented at the Proceedings of the British Congress for Mathematics Education (BCME) (pp. 159-166), Manchester.

Pampaka, M., Williams, J. S., Hutchenson, G., Black, L., Davis , P., Hernandez-Martines, P., & Wake, G. (2013). Measuring Alternative Learning Outcomes: Dispositions to Study in Higher Education. Journal of Applied Measurement, 14(2), 197-218.

Pampaka, M., Williams, J. S., Hutcheson, G., Wake, G., Black, L., Davis, P., & Hernandez - Martinez, P. (2012). The association between mathematics pedagogy and learners' dispositions for university study. British Educational Research Journal, 38(3), 473-496.

Pancer, S. M., Hunsberger, B., Pratt, M. W., & Alisat, S. (2000). Cognitive complexity of expectations and adjustment to university in the first year. Journal of Adolescent Research, 15(1), 38-55.

Peat, M., Dalziel, J., & Grant, A. M. (2000). Enhancing the transition to university by facilitating social and study networks: Results of a one-day workshop. Innovations in Education and Teaching International, 37(4), 293-303.

Scanlon, L., Rowling, L., & Weber, Z. (2007). 'You don't have like an identity you are just lost in a crowd': Forming a Student Identity in the First-year Transition to University. Journal of Youth Studies, 10(2), 223-241.

Schworm, S., & Gruber, H. (2012). E-Learning in universities: Supporting help-seeking processes by instructional prompts. British Journal of Educational Technology, 43(2), 272-281.

Shah, C., & Burke, G. (1999). An Undergraduate Student Flow Model: Australian Higher Education. Higher Education, 37(4), 359-375.

Smyth, L., Mavor, K. I., Platow, M. J., Grace, D. M., & Reynolds, K. J. (2013). Discipline social identification, study norms and learning approach in university students. Educational Psychology, 1-21.

Thissen, D., Steinberg, L., & Wainer, H. (1993). Detection of Differential Item Functioning Using the Parameters of Item Response Models. In P. W. Holland & H. Wainer (Eds.), Differential Item Functioning (pp. 67-114). London Lawrence Erlbaum Associates, Publishers.

Tormey, R. (2013). The centre cannot hold: untangling two different trajectories of the 'approaches to learning' framework. Teaching in Higher Education, 19(1), 1-12.

Weiner-Levy, N. (2008). Universities as a meeting point with new academic knowledge, society and culture: Cognitive and emotional transitions during higher education. Cambridge Journal of Education, 38(4), 497-512.

Weisberg, S. (1985). Applied Linear Regression (second edition): John Wiley & Sons.

Williams, J. S. (2012). Use and exchange value in mathematics education: contemporary CHAT meets Bourdieu's sociology. Educational Studies in Mathematics, 80(1-2), 147-168.

Williams, J. S., Black, L., Hernandez-Martinez, P., Davis, P., Pampaka, M., & Wake, G. (2009). Repertoires of aspiration, narratives of identity, and cultural models of mathematics in practice. In M. César & K. Kumpulainen (Eds.), Social Interactions in Multicultural Settings (pp. 39-69). Rotterdam: Sense. Publishers.

Wingate, U. (2007). A Framework for Transition: Supporting 'Learning to Learn' in Higher Education. Higher Education Quarterly, 61(3), 391-405.

Wolfe, E. W., & Smith Jr., E. V. (2007a). Instrument Development Tools and Activities for Measure Validation Using Rasch Models: Part I - Instrument Development Tools. Journal of Applied Measurement, 8(1), 97-123.

Wolfe, E. W., & Smith Jr., E. V. (2007b). Instrument Development Tools and Activities for Measure Validation Using Rasch Models: Part II - Validation Activities. Journal of Applied Measurement, 8(2), 204-234.

Wright, B. D. (1999). Rasch Measurement Models. In G. N. Masters & J. P. Keeves (Eds.), Advances in Measurement in Educational Research and Assessment (pp. 268-281). Oxford: Pergamon.

Wright, B. D., & Masters, G. N. (1982). Rating Scale Analysis. Chicago: MESA Press.

Wright, B. D., & Mok, M. (2000). Rasch Models Overview. Journal of Applied Measurement, 1(1), 83-106

[-]

recommendations

 

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro completo del ítem