The focus of the article is the validation of an instrument to assess gifted students’ affect after mathematical problem solving tasks. Participants were 225 students identified by their district as gifted in grades four to six. The Chamberlin Affective Instrument for Mathematical Problem Solving was used to assess feelings, emotions, and dispositions after students solved model-eliciting activities in groups of three. Through the use of principal component analysis, it was determined that three factors should be retained. The instrument holds promise because it may be used to assess affect, which has implications for identification and curricular adjustments to optimize affect.
AikenL (1974) Two scales of attitude toward mathematics. Journal for Research in Mathematics Education5: 67–71.
2.
AndersonLWBourkeSF (2000) Assessing Affective Characteristics in the Schools. Mahwah, NJ: Lawrence Erlbaum Associates.
3.
BauerJDJacksonASkwarchukMZelefskyM (2006) Principal component, Varimax rotation and cost analysis of volume effects in rectal bleeding in patients treated with 3D-CRT for prostate cancer. Physics in Medicine and Biology51: 5105–5123.
4.
BinetASimonT (1916) The Development of Intelligence in Children. Baltimore, MD: Williams & Wilkins. (Reprinted 1973, New York: Arno Press; 1983, Salem, NH: Ayer Company.)
5.
CattellR (1966) The scree test for the number of factors. Multivariate Behavioral Research1: 245–276.
6.
ChamberlinSA (2002) Analysis of interest during and after model-eliciting activities: A comparison of gifted and general population students (Doctoral dissertation, Purdue University, 2002). Dissertation Abstracts International64: 2379.
7.
ChamberlinSA (2006) Gifted and talented teachers’ and coordinators’ perspectives of affect and mathematical problem solving in middle grade gifted programs in the United States. Australasian Journal of Gifted Education15: 32–38.
ChamberlinSAMoonSM (2005) Model-eliciting activities: An introduction to gifted education. Journal of Secondary Gifted Education17: 37–47.
10.
FennemaEShermanJA (1976) Fennema–Sherman mathematics attitudes scales: Instruments designed to measure attitudes towards the learning of mathematics by females and males. Journal for Research in Mathematics Education7: 324–326.
11.
FishbeinMAjzenI (1975) Belief, attitude, attention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
12.
ForgaszHJLederGCGardnerPL (1999) The Fennema–Sherman mathematics as a male domain scale re-examined. The Journal for Research in Mathematics Education30: 342–348.
13.
GetzelsJW (1966) The problem of interests: A reconsideration. Supplementary Education Monographs66: 97–106.
14.
HallCSLindzeyG (1970) Theories of Personality. 2nd ed. New York: John Wiley and Sons.
15.
HartLEWalkerJ (1993) The role of affect in teaching and learning mathematics. In: OwensDT (ed.) Research Ideas for the Classroom: Middle Grades Mathematics. New York: MacMillan Publishing, pp. 22–38.
16.
HigginsJL (1970) Attitude changes in a mathematics library utilizing a mathematics through science approach. Journal for Research in Mathematics Education7: 43–56.
17.
HoffmanML (1986) Affect, cognition, and motivation. In: SorrentinoRMHigginsET (eds.) Handbook of Motivation and Cognition: Foundations of Social Behavior. New York: The Guilford Press, pp. 244–280.
18.
HuckS (2007) Reading Statistics and Research. 5th ed. New York: Allyn & Bacon.
19.
LeshRHooverMHoleBKellyAPostT (2000) Principles for developing thought-revealing activities for students and teachers. In: KellyALeshR (eds.) The Handbook of Research Design in Mathematics and Science Education. Hillsdale, NJ: Lawrence Erlbaum and Associates, pp. 591–646.
20.
LidzCSMacrineSL (2001) An alternative approach to the identification of gifted culturally and linguistically diverse learners: The contribution of dynamic assessment. School Psychology International22: 74–96.
21.
McLeodDBAdamsVM (1989) Affect and Mathematical Problem Solving: A New Perspective. New York: Springer-Verlag.
22.
MessickS (1979) Potential uses of non-cognitive measurement in education. Journal of Educational Psychology71: 281–292.
23.
National Council of Supervisors of Mathematics (1978) Position statements on basic skills. Mathematics Teacher71: 147–152.
24.
National Council of Teachers of Mathematics (1980) An Agenda for Action: Recommendations for School Mathematics of the 1980s. Reston, VA: NCTM.
25.
National Council of Teachers of Mathematics (1989) Curriculum and Evaluation Standards for School Mathematics. Reston, VA: NCTM.
26.
National Council of Teachers of Mathematics (2000) Principles and Standards for School Mathematics. Reston, VA: NCTM.
27.
PajaresF (1996) Self-efficacy beliefs and mathematical problem solving of gifted students. Contemporary Educational Psychology21: 325–344.
28.
PajaresFMillerMD (1995) Mathematics self-efficacy and mathematics performances: The need for specificity of assessment. Journal of Counseling Psychology42: 190–198.
29.
RichardsonFCSuinnRM (1972) The Mathematics Anxiety Rating Scale: Psychometric data. Journal of Counseling Psychology19: 551–554.
30.
RomeyEA (2006) A quantitative study of the Alabama Gifted Matrix Identification Process: Implications for underserved populations. Unpublished doctoral dissertation, University of Connecticut, Storrs.
31.
ShavelsonRJHubnerJJStantonGC (1976) Self-concept: Validation of construct interpretations. Review of Educational Research46: 407–441.
32.
StellefsonMHanikB (2008, February) Strategies for determining the number of factors to retain in exploratory factor analysis. Paper presented at the annual meeting of the Southwest Educational Research Association, New Orleans, LA.
33.
SuhrDD (2005, April). Principal component analysis versus exploratory factor analysis. Paper presented at SAS Users Group International (SUGI), Philadelphia, PA. Available at: http://www2.sas.com/proceedings/sugi30/203-30.pdf(accessed 1 March 2011).
34.
SuinnRMEdwardsR (1982) The measurement of math anxiety: The Mathematics Anxiety Rating Scale for Adolescents MARS-A. Journals of Clinical Psychology38: 576–580.
35.
TangumaJ (2000, February). Determining the number of factors to retain. Paper presented at the annual meeting of the Southwest Educational Research Association, Dallas, TX.
36.
TapiaMMarshGE2nd (2004) An instrument to measure mathematics attitudes. Academic Exchange Quarterly8: 16–21.
37.
ThompsonAG (1992) Teachers’ beliefs and conceptions: A synthesis of the research. In: GrouwsDA (ed.) Handbook of Research on Mathematics Learning and Teaching. New York: MacMillan, pp. 127–146.
38.
TylerRW (1973) Assessing educational achievement in the affective domain. Measurement in Education4: 108.
39.
WeinerB (1992) Motivation. In: AlkinM (ed.) Encyclopedia of Educational Research. 4th ed. New York: MacMillan, pp. 860–865.
