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At-Risk Adolescents Perceptions of Learning Temperaments: Implications for Educational Intervention.

The current study examined learning temperaments and needs differences between at-risk students receiving psychosocial and academic interventions with an average performing comparison group. In all, 293 males and 408 females, consisting of 472 at-risk, and 229 comparison students were surveyed. Dependent measures were obtained through administration of the Nunn Assessment of Learning Temperament (NALT). Results indicated significant main and interaction effects. Implications for educational intervention are discussed.

Temperamental and self-perception differences continue to receive intense interest in the psychoeducational literature (Brophy, 1996; Carey, 1998; Nunn & Parish, 1992; Rothbart & Jones, 1998). Studies of learning have long emphasized the role that temperamental characteristics, perception of needs, and accommodating for these differences can play in facilitating successful response to the learning environment (Ackerman, Kyllonen, & Roberts, 1999; Nunn, 1995). As Carey (1998) has noted, "Certain temperament traits ... are particularly likely to create a `poor fit' with the caregiving environment and generate the dissonance and excessive stress that lead to behavioral or other functional problems in the child" (pg. 527). Currently, American education is challenged to fulfill the needs of students termed "at-risk," in order to capture talents and human resources. Discerning temperaments of at-risk youth relative to learning and instructional practices is a productive avenue in which actions can be taken to facilitate each students' unique approach to the learning environment (Barr & Barrett, 1995; Mills, Dunham, & Alpert, 1988; Sartain, 1989; Slavin, Karweit, & Madden, 1989).

In this respect, middle to late adolescence presents some of the greatest challenges to educators as they attempt to accommodate for temperamental considerations (Brophy, 1996; Nunn, 1995). As such, adolescence is an opportunity in which support of learning temperaments is helpful to both educators and students alike. Such individualization is proactive in nature and emphasizes the importance of working with student affinities (Levine, 1994). The present study attempts to further define at-risk adolescents' perceptions of temperaments in an effort to clarify how best to support their success.

Method

Participants

Students attending a large mid-west high school in grades 10 through 12 (N = 701) voluntarily participated in this study. In all, 293 males and 408 females, consisting of 472 at-risk, and 229 comparison students were surveyed. Students in this study were primarily caucasian, and from middle to lower-middle income backgrounds.

Instrument

The Nunn Assessment of Learning Temperament-NALT (Nunn, 1995) was administered as a measure of dependent variables. The NALT is a likert-type scale consisting of 110 items representing seven oblique factors that have demonstrated satisfactory statistical validity (Nunn, 1995), and reliability (Nunn, 1992).

Procedure

Students meeting criteria for "at-risk" were those who had demonstrated the following: a) average academic performance in the last three semesters one standard deviation or more below their peers; and b) receiving one or more academic and/or behavioral support service through the schools' at-risk program. All students completed the NALT individually or in small groups during the school day. All responses were confidential with parental permission obtained prior to completion of the instruments.

Results

Two-way analysis of variance was employed to examine the effects of gender and at-risk status upon NALT factors. Regarding Achievement Orientation (AO), a main effect for at-risk was obtained, F (1,518) = 42.81, p [is less than] .0001, with at-risk students being significantly less achievement oriented (M = 27.55) than were the comparison group (M = 30.79). Main effects for gender and interaction were nonsignificant. Anxiety in Performance Situations (APS) also revealed a significant effect for gender, F(1,518) = 39.22, p [is less than] .0001 with females demonstrating significantly higher scores on this measure (M = 33.83) than did males (M = 28.38). Nonsignificant effects for at-risk status and interactions were obtained. Adolescent scores on the Conceptual Level Concrete (CLC) variable, indicated significant variance as a function of at-risk status F(1,513) = 4.45, p [is less than] .03, with at-risk students indicating a lesser need for concreteness in their learning experiences (M = 11.02) than did the comparison group (M = 11.81), with no other main or interaction effects obtained. Similarly, the Informal Learning Style (ILS) factor indicated greater desire for informal learning conditions for at-risk students (M = 20.05) than for comparisons (M = 17.34), F = (1,513) = 28.37, p [is less than] .00001. Kinesthetic Style (KS) revealed both main and interaction effects. A main effect for gender F(1, 513) = 15.58, p [is less than] .0001, and for Gender X at-risk were obtained F(1,513) = 5.48, p [is less than] .05. The main effect for gender revealed that males preferred more physical/kinesthetic movement (M = 22.79) in their learning experiences than did females (M = 20.42), The interaction effect for gender and at-risk F(1,693) = 6.39, p [is less than] .05) revealed that both male (M = 22.63) and female (M = 22.05) at-risk students preferred significantly more kinesthetic sensation and physical movement in their learning than did male (M = 20.22) and female (M = 20.40) peers, but were not significantly different from each other.

Self-Concept as a Learner (SCL) revealed significant main effects for gender and for at-risk. Specifically, the main effect for gender F(1,518), = 16.03 p [is less than] .0001, revealed that males (M = 22.35) held higher SCL than did females (M = 20.28). The main effect for at-risk status F(1,518) F = 45.21 indicated that at-risk students (M = 19.69) as compared to comparisons (M = 23.81) perceived themselves less favorably as learners.

Discussion

Results of the current study reveal interesting differences when comparing at-risk students and their peers on several learning temperament factors. This is consistent with previous research that has found differences between students at-risk for academic difficulties, and those who were not (Manning & Baruth, 1995; Nunn, 1995) Indeed, for five of the seven temperamental factors associated with learning preferences, at-risk students perceived themselves differently than nonidentified adolescents. These findings put into focus the importance of considering temperamental variability in approaching and providing educational experiences for these students. Contemporary research has shown the utility of working to understand and apply what is known by such differences in disposition to working hypotheses regarding teacher-student interactions including expectations and predictions regarding behavior.

Working Hypothesis 1: At-risk students learning temperaments reveal lesser tendencies for orienting toward goals, persevering in the face of failure, and demonstrating self-initiative. The current findings revealed significantly less tendency for achievement orientation in the at-risk students sampled. Educational systems must examine alternatives to orient at-risk students toward future goals and realities. Students in this study were significantly lower in their aspirations toward long-term goals, or goal-directedness. Elements such as the need to achieve, perseverance in face of failure, and self-initiative have not been learned or generally rewarded in these students. Educational practices should not assume that at-risk students `should' have these qualities, but can work toward nurturing them (Covington, 1998).

Working Hypothesis 2: At-risk students learning temperaments reveal a preference for broader conceptual schemas, less fact-based approaches, and greater emphasis upon the underlying ideas and relevancy of what is taught. Results indicated that at-risk students preferred less concreteness and structure in their learning experiences while comparison peers perceived a greater need for the presentation of `facts' vs. theories in their learning. It would appear that at-risk students may not learn traditional concepts in the common linear, piecemeal, and fact-oriented way that many mainstream students do. It would be a viable opportunity to provide at-risk students with other avenues of learning `factual' materials, such as discussion, guided discovery, or Socratic methods in which they may approach the task from a more abstract direction, making broad inferences and getting the `big picture' first before attempting to integrate the specifics.

Working Hypothesis 3: At-risk students reveal a temperament that values the informality and comfort of the learning environment. This finding indicates that our at-risk group found the prospect of learning within a formal atmosphere less preferable than one in which they were afforded the opportunity to move, sit, listen to music, eat and do various activities not available in a traditional classroom setting. It is not surprising that they would report this preference, but what is significant is that they appear to need this environment to a greater degree or have less tolerance than their more successful school peers. These incidental elements of the learning environment may seem inconsequential to many, however the at-risk student perceived them as important elements related to their success in learning.

Working Hypothesis 4: At-risk students as compared to their peers, describe their temperaments as needing more physical sensation, movement, and direct engagement with learning materials. At-risk students indicated a greater desire to experience physical movement, sensation, and the manipulation of learning materials than did their peers. These students reported that a positive learning setting would included the opportunity to engage in moving about the classroom, in touching, constructing, and physically engaging in an active sense the learning activities. The comparison group perceived less of a need for this, and were more acceptant of a passive, less physical approach to learning.

Working Hypothesis 5: Temperamentally, at-risk students view themselves experiencing chronic failure, finding school a difficult experience, and less academically competent than their peers. This studies results indicate the general finding that at-risk students simply view themselves as less competent than their peers. This is an issue that affects self-motivation and most probably interferes with the students ability to act in a self-directed way (Bandura, 1997). Educators and others should assist the at-risk student in determining their own unique academic affinities and strengths rather than making comparisons with the traditional generic comparison that they may be making.

The working hypotheses above are in need of further research to examine their predictive relationship with other indices of student adjustment such as grades, attendance, school behavior, and the like. From a heuristic standpoint however, the current findings support the impression that educators could profit from considering ways in which expectations, interactions, and accommodations could be arranged for the low-achieving at-risk student in their classrooms. Given the immense economic and social costs of underachievement and school dropouts in our society, diligent efforts in this regard can only be applauded (Barr & Barrett, 1995).

[Figure 1-3 ILLUSTRATION OMITTED]

Table 1 Factors and test-retest reliabilities for the Nunn Assessment of Learning
Temperament and Needs

 NALT Factor Item Examples Test-retest
 Reliability

Achievement * I have a high need to achieve. .69
 Orientation * Once I begin a project,
 I always finish it.
 * I am best described as
 a "self-starter."

Anxiety in * I become overexcited easily. .71
 Performance * I get embarrassed easily.
 Situations * I get so nervous when
 I take a test that I
 forget what I studied.

Behavioral * I would describe my behavior as .68
 Impulsivity in unpredictable."
 Learning * Sometimes I just can't
 seem to control my
 actions.
 * Most people would
 describe me as
 "impulsive."

Concrete * I am more interested in .79
 Conceptual facts than ideas.
 Learning * I learn best when things
 are presented in
 a concrete way.
 * I learn facts better
 than theories.

Informal * I don't study well at a desk. .70
 Learning * I prefer studying in
 Environment a comfortable chair.
 * I like to hear background
 music when I study.

Kinesthetic * I enjoy movement and .77
 Learning activity in learning.
 * I learn more with my
 "hands" than with my "head."
 * I learn best by feeling,
 touching, and moving things.

Self- * School has always been .81
 Perception very easy for me.
 as a * I can learn things as easily
 Learner as anyone else.
 * I have a very positive
 view of myself as a learner.


Table 2 Validity coefficients between NALT and other psychosocial indices
NALT Personal Rotter I-E Perfectionism
Factor Attribute Scale Scale
 Inventory

Achievement -.51 -.38 -.36
Orientation N = 742 N = 742 N = 743
 p<.0001 p<.0001 p<.0001

Anxiety in .45 .31 .44
Performance N = 742 N = 742 N = 743
Situations p<.0001 p<.0001 p<.0001

Behavioral .36 .44 .55
Tempo- N =748 N = 748 N = 743
Impulsivity p<.0001 p<.0001 p<.0001

Conceptual .02 .02 .03
Level Concrete N = 748 N = 751 N = 743
 p = .55 p = .57 p = .49

Informal .10 .18 .54
Learning Style N = 748 N = 748 N = 743
 p<.05 p<.0001 p<. 0001

Kinesthetic Style .05 .01 .35
 N = 737 N = 746 N = 743
 p = .14 p = .88 p<.0001

Self-Concept as a .58 -.49 .24
Learner N =744 N = 744 N = 743
 p<.0001 p<.0001 p<.0001


References

Ackerman, P; Kyllonen, P. & Roberts, R. (1999). Learning and individual differences. Washington, D.C.: American Psychological Association.

Barr, R. & Barrett, W. (1995). Hope at last for at-risk youth. Boston, MA: Allyn & Bacon.

Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W.H. Freeman & Company.

Brophy, E.J. (1996). Teaching problem students. New York: Guilford Press.

Carey, W. (1998). Temperament and behavior problems in the classroom. School Psychology Review, 27, 522-533.

Covington, M.V. (1998). The will to learn: A guide for motivating young people. Cambridge: Cambridge University Press.

Levine, M.D. (1994). Educational care: A system for understanding and helping children with learning problems at home and in school. Cambridge: Educators Publishing Service, Inc.

Manning, M. & Baruth, L. (1995). Students at risk. Boston, MA: Allyn & Bacon.

McClowry, (1998).

Mills, R., Dunham, R., & Alpert, G.(1988). Working with high-risk youth in prevention and early intervention programs: Toward a comprehensive wellness model. Adolescence, 23, 643660.

Nunn, G.D. & Parish, T.S. (1992). The psychosocial characteristics of at-risk high school students. Adolescence, 27, 435-440.

Nunn, G.D. (1995). Effects of a learning styles and strategies intervention upon at-risk middle school students achievement and locus of control. Journal of Instructional Psychology, 22, 34-39.

Rothbart, M. & Jones, L. (1998). Temperament, self-regulation, and education. School Psychology Review, 27, 479-491.

Sartain, H. (1989). Nonachieving students at-risk. Washington, D.C.: National Education Association.

Shaffer, D.R. (1999). Developmental psychology: Childhood and adolescence. Pacific Grove, CA: Brooks/Cole.

Dr. Gerald D. Nunn, faculty, Idaho State University. Merilee Miller, G.A., Idaho State University

Correspondence concerning this article should be addressed to Dr. Gerald D. Nunn, School Psychology Program, Idaho State University, Box 8059, Pocatello, ID 83209
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Author:Miller, Merilee
Publication:Journal of Instructional Psychology
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Date:Dec 1, 2000
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