Evaluating a metacognitive and planned happenstance career training course for Taiwanese college students.
Because of technological advances, people are now progressing from the late industrial era to a new informational era (Stage & Dean, 2000). Although high technology makes lives more convenient than ever before, living in the information age inevitably brings turbulence and uncertainty. To help individuals form better career paths and lead meaningful lives in the 21st century, career practitioners and theorists are developing and refining effective career-related interventions to improve people's career decision-making competencies (Griffin & Hesketh, 2003; Spokane, Fouad, & Swanson, 2003).
Research has clearly demonstrated positive outcomes for career interventions (Thomas & McDaniel, 2004; Tinsley, Tinsley, & Rushing, 2002; Vernick, Reardon, & Sampson, 2004; Wessel, Christian, & Hoff, 2003; Whiston, Brecheisen, & Stephens, 2003). Career-related interventions have become increasingly common and successful. On the other hand, some career researchers and/or practitioners have proposed that career decision making and development might not be linear and further postulated the importance of investigating the impact of chance events on an individual's career path (Betsworth & Hanson, 1996; Cabral & Salomone, 1990; Krumbohz & Levin, 2004; Magnuson, Wilcoxon, & Norem, 2003; Mitchell, Levin, & Krumboltz, 1999; Pelsma & Arnett, 2002; Pryor & Bright, 2003; Scott & Hatalla, 1990; E. N. Williams et al., 1998). However, an examination of the literature on the impact of chance events demonstrates that many career-related interventions do not seem to rise above the conceptual level. Few articles have investigated implementing planned chance as a factor in career development (Betsworth & Hanson, 1996; Hart, Rayner, & Christensen, 1971; Scott & Hatalla, 1990; E. N. Williams et al., 1998). Furthermore, none of these researchers evaluated how to optimize the benefit of using chance events to enhance people's career capabilities in a career development training course.
Nevertheless, in their planned happenstance theory, Mitchell et al. (1999) proposed that because of the rapid shifts in the world of work, chance events should no longer be ignored in the process of career counseling; on the contrary, both clients and career counselors should regard the chance factor as inevitable and desirable. More important, Mitchell et al. highlighted the need to help clients capitalize on chance events to broaden their career potential. The purpose of planned happenstance theory was to "assist clients to generate, recognize, and incorporate chance events into their career development" (Mitchell et al., 1999, p. 117). Specifically, this theory initially emphasized the importance of understanding an individual's personal experiences. In addition, it detailed ways for the individual to frame events as meaningful learning opportunities, engage in self-encouragement, use cognitive restructuring, and capitalize on positive chance events. In this manner, people could broaden their visions and take positive actions toward an unforeseen future. This might prepare them to overcome career obstacles and attain their desired career goals. In other words, in comparison with other chance approaches, the planned happenstance theory not only takes into account the chance factor in career development but also provides a series of guidelines for clients to use in taking constructive action and creating opportunities for achieving personal goals. Therefore, the planned happenstance theory may be an effective career development tool that works well in the information age.
According to Mitchell et al.'s (1999) happenstance approach, learning plays a pivotal role in one's career development. Accordingly, people should recognize and incorporate chance events into their lives with sufficient scope and depth. Hence, if people have a framework to increase their capacity to learn, to be metacognitive (i.e., think about how they are thinking), and to question how chance events influence their lives, they will be better prepared to make the most of their unique turns of life and, accordingly, their careers. To enhance an individual's ability to learn, many educators have incorporated metacognition into the teaching process. The results of numerous studies have shown that instruction in metacoguitive processes can promote learning and problem solving among students and improve existing metacognitive strategies and models (Davidson & Sternberg, 1998; Desoete, Roeyers, & De Clercq, 2003; Dhieb-Henia, 2003; Hartman, 2001; Hollingworth & McLoughlin, 2001; McWhaw & Abrami, 2001; Sheorey & Mokhtari, 2001; Teong, 2003; W. M. Williams et al., 2002; Wohers, 2003; Wright & Jacobs, 2003).
Davidson and Sternberg (1998) proposed eight relevant factors that could influence how well people use metacognition in problem solving: (a) encoding, (b) mental representation, (c) representational change, (d) domain specificity, (e) planning for goals, (f) use of heuristics, (g) transfer of skills, and (h) obstacles awareness. Metacognition training in a practical sense involves structured experiences in which students engage in thinking about their own thoughts, achieving an awareness of themselves as actors in their environments and the ability to regulate and manage their cognitions. Activities have been designed that teachers can implement to provide opportunities for self-assessment, self-questioning, and the thinking aloud method to facilitate students' metacognitive knowledge and skills in learning (Hartman, 2001).
The purpose of this research was to use a pretest-posttest, nonequivalent control group, quasi-experimental design to evaluate the effectiveness (as measured by various career competency measures) of a two-credit, 12-week career course for Taiwanese college students. The material for the career course was based on a combination of the planned happenstance theory and Davidson and Sternberg's (1998) metacognitive problem-solving process. The research questions were
1. What differences existed in the performance on the Tennessee Self-Concept Scale: Second Edition for Adults (TSCS: 2), the Learning and Study Strategies Inventory (LASSI), and the Metacognitive Competency Measure (MCM) among the four groups (two treatment groups, one comparison group, and one control group) after the two treatment groups were given the career intervention?
2. What differences existed among the treatment, comparison, and control groups on a Course Evaluation Measure (CEM)?
3. Was there a significant difference between a treatment group and a control group in the frequency of attendance at a mock interview activity?
For this study, four classes from a Taiwanese college were chosen to identify the treatment effects of the career intervention. The participants were all Taiwanese college students (N = 157), with men (n = 107) representing a majority. Most participants were majoring in electrical engineering (n = 123) or nursing. A majority were sophomores (n = 83), and the remainder were seniors. Participants belonged to a daytime treatment group (DTG; n = 31) with a mean age of 19.84 years (SD = .90), a nighttime treatment group (NTG; n = 40) with a mean age of 28.07 (SD = 4.00), a nighttime comparison group (NCG; n = 34) with a mean age of 26.50 (SD = 3.50), or a daytime nonequivalent control group (DCG; n = 52) with a mean age of 19.75 (SD = .71) in this pretest-posttest, nonequivalent control group, quasi-experimental design. Note that members of the DCG were also participants in the no-treatment control group, but that the NCG members were in a career development strategy class. Each member of the four groups completed a consent form before participating in this research, and none of the participants received any monetary compensation or extra credit.
To evaluate the effectiveness of the metacognitive career training, metacognitive, cognitive, affective, and behavioral dimensions of student performance and development were assessed in this study. Accordingly, four instruments were used: (a) the TSCS: 2; (b) the LASSI, using the Motivation, Time Management, and Solving-Learning-Problems subscales; (c) the MCM; and, (d) a CEM. A Mock Interview Attendance Measure was also used to examine the treatment effects.
TSCS: 2. The TSCS: 2 was originally developed by Fitts and Warren (1996). The Mandarin Chinese (predominant language of Taiwan) version of the TSCS: 2 is a 5-point, 82-item, self-rating scale that was modified by Lin, Chang, and Chen (2000) to assess how adults feel about themselves. The Cronbach's alpha coefficients of the TSCS: 2 varied from .75 to .92, thus indicating adequate reliability (Lin et al., 2000). A principal component analysis with varimax rotation was also used to test the construct validity of the instrument. The results showed the existence of six clusters: Physical, Moral, Family, Social, Academic, and Personal (Lin et al., 2000). Thus, the TSCS: 2 was able to measure the dimension of interest. In this study, the total scores (T scores) derived from the TSCS: 2 were used as the overall measure of a participant's self-perception. In general, within a certain range, higher T scores on the TSCS: 2 indicate that the participants hold positive perceptions about themselves.
LASSI. The initial version of the LASSI was developed in 1987 by Weinstein, Palmer, and Schulte. It has been generally regarded as a valid and reliable tool for assessing students' learning and studying strategies (Weinstein et al., 1987). The modified Mandarin Chinese version of the LASSI is a 5-point, 87-item assessment scale for college students used to evaluate their study habits and strategies in 11 areas. Only selected subscales were used in this study: Motivation, Time Management, and Solving-Learning-Problems. A higher percentile rank score on the LASSI indicates more positive learning experiences and more frequent use of systematic study strategies. The Cronbach's alpha coefficients for the subscales of the LASSI ranged from .62 to .82, thus indicating adequate reliability (Lee, Chang, & Hung, 1991). A principal component analysis with varimax rotation identified 11 factors for the LASSI that explained 42.8% of the total variance (Lee et al., 1991), further indicating its validity.
MCM. This instrument was developed by the first author of this article to measure each participant's response to a critical incident in career problem solving. The MCM consists of a brief description of a career indecision situation on campus and two follow-up questions for participants to answer. Specifically, participants were asked to identify which decision was most appropriate in response to the career dilemma presented and to state the reasons for their response. Furthermore, each participant was asked to design a career project that would assist an individual represented in a case scenario to reach a predetermined career goal. Two raters with master's degrees and more than 5 years of counseling experience independently evaluated all of the MCM results. The total scores on the MCM were analyzed to determine if differences existed among the four groups' metacognitive competency in career problem solving. The intraclass r (Shrout & Fleiss Model 2) was used to examine the degree of similarity between two raters (Shrout & Fleiss, 1979). The intraclass r was .96 for all of the MCM results, r (282) = .96, p < .01, indicating high interrater reliability.
CEM. CEM was designed by the first author of this article to evaluate the degree to which the participants found the career course valuable and/or helpful. It is composed of three parts: the course's absenteeism rate, measured by self-report; 20 self-report questions evaluating the effectiveness of the course, and an open-ended question for students to provide any additional comments. The 20 self-report questions consist of 10 items evaluating the career training materials, 5 items rating the instructor's proficiency, and 5 items rating the quality of the teacher-student interactions. Students recorded their responses on a 5-point Likert scale: 1 (strongly disagree) to 5 (strongly agree); total scores ranged from 20 to 100, with higher scores indicating more positive course experiences.
The Mock Interview Attendance Measure. This instrument measured how many DTG students versus DCG students would actually capitalize on this chance event and attend the one-on-one mock interview activity. In fact, this activity was open to all of the daytime students. In preparation for this activity, all of the interviewees were required to hand in their resumes and autobiographies in advance. Moreover, each of the interviewees would receive an interview assessment feedback sheet immediately after the activity.
Procedure and Data Collection
The treatment consisted of a two-credit, 12-week career course for the daytime (elective course) and nighttime (required course) students conducted by the first author who had at least 8 years of practical career counseling experience working with Taiwanese people ranging from 20 to 50 years of age. The content of the learning units was (a) Course Overview; (b) Career Turning Points Exploration; (c) Self-Awareness, Analysis, and Growth; (d) Work World Exploration and Capitalizing on the Opportunities; (e) Making Yourself Marketable for Careers; (f) Time Is Life--Time Management; (g) Career and Mental Health--Coping With Stress; (h) Combating Career Myths; (i) Smart Problem Solving; and (j) Career Decision Making. In addition, each student had to hand in six assignments: a personal learning history, a self-analysis report, an autobiography and resume, a book review/reflection, and a personal career action plan. The TSCS: 2, LASSI, and MCM were completed at the beginning of the course and again at the end of the course by both the experimental and the control groups.
The four groups had unequal pretest means on the measures. Hence, comparative analysis was done using an analysis of variance (ANOVA) on the gain scores, which consisted of the pretest scores subtracted from the posttest scores for the four groups. The Sidak correction was used for post hoc multiple comparisons to determine which groups' gain scores were significantly different.
Comparisons of Groups
ANOVAs computed on the gain scores determined whether there were differences among the four groups on the TSCS: 2; the LASSI subscales Motivation, Time Management, and Solving-Learning-Problems; and the MCM (see Table 1).
Post hoc analyses using the Sidak correction showed significant gain score differences between treatment, control, and comparison groups on the TSCS: 2, with the DTG (M = 3.23, SD = 5.29) and NTG (M = 3.92, SD = 5.50) scores being significantly greater than the DCG (M = .84, SD = 4.70) and NCG (M = .37, SD = 5.06) scores. Analyses for the Motivation subscale of the LASSI indicated that the DTG (M = 11.69, SD = 23.30) and NTG (M = 11.12, SD = 23.10) scores were significantly greater than the NCG (M = -5.32, SD = 17.70) score. Comparisons of the groups' scores for the Time Management subscale indicated significant differences between the DTG (M = 7.90, SD = 16.33) and the NTG (M = 10.37, SD = 24.87) scores as compared to the DCG (M = -3.13, SD = 19.21) score. Post hoc comparisons on the Solving-Learning-Problems subscale of the LASSI reported significant differences only between the NTG (M = 13.30, SD = 26.71) score and the DCG (M= -3.56, SD = 26.00) score. Last, comparisons on the MCM reported significant differences between the DTG (M = 2.88, SD = 5.57) score, the NTG (M = 3.16, SD = 4.45) score, and the NCG (M = 3.21, SD = 5.14) score as compared to the DCG (M = -1.21, SD = 4.52) score. There was a significant difference on the CEM: F(2, 109) = 14.89, p < .01. The Games-Howell procedure was used for multiple comparisons to adjust for the problem of unequal variances and sample sizes. The follow-up tests showed that the NTG (M = 85.05, SD = 8.13) score and the DTG (M = 81.32, SD = 9.11) score gained more significantly on the CEM than did the NCG (M = 72.87, SD = 12.63) score. There were 24 mock interview application forms; 1 student did not come to the activity on the scheduled day. Among the 23 remaining students, 22 students from the experimental group, DTG, obtained mock interview applications, and 21 participated in interviews. None of the interviewees were from the DCG. The mock interview attendance proportions of the experimental group, DTG, and the DCG were 68% and 0%, respectively. A two-way contingency table analysis demonstrated that type of group and attendance were significantly related: Pearson [chi square] (1, N = 83) = 47.16, p < .01, Cramer's V = .75. In other words, there was a greater probability of members of the DTG attending mock interviews than of DCG members attending.
The results of this study must be interpreted with a degree of caution; random sampling was not achieved. It would be difficult to conclude that the effects could be generalized to a broader population because the experiment was conducted at a single institution and the participants were Taiwanese, adults, and college educated. However, the findings might be generalized to participants of the study who shared similar characteristics.
Generally, the findings demonstrated positive results for a career development training course based on a planned happenstance career theory and using metacognitive strategies to develop problem-solving and decision-making skills. Five measures indicated significant pre- to posttest changes for the treatment groups. These changes were also validated by the stable scores of the comparison and/or the nonequivalent control groups.
Both treatment groups, the DTG and the NTG, showed significant positive gains on the MCM; however, the NCG also reported significant gains over and above those made by the DCG. The mixed results on the MCM may be explained by the participants' enrollment in a career development strategy class. Perhaps the career development strategy class of the comparison group had produced enough of an incidental effect in the metacognitive area for students to more positively respond to the critical incident. Nevertheless, the notable gains of the treatment groups (DTG and NTG) on the TSCS: 2 and the LASSI subscales of Motivation, Time Management, and Solving-Learning-Problems, plus significantly higher gains on the CEM over the gains of the NCG, indicated that perhaps the metacognitive strategies covered gave the treatment groups better preparation than the comparison groups.
Last, unlike most career intervention studies, this research was unique in that it measured participants' actual behavioral responses to a mock interview activity. With the assistance of the metacognitive career training course, about 68% of the DTG students moved from "notion to motion" (i.e., idea to action). These results indeed supported the essence of Mitchell et al.'s (1999) planned happenstance theory, which emphasized the importance of equipping individuals with the skills to take advantage of the chance events that would increase an individual's career development and career adaptability.
A significant implication of this study is that people often tend to overemphasize chance in their lives (e.g., waiting for a big lottery payoff), or they might err by minimizing chance events. However, by using the metacognitive strategies of self-assessment, self-questioning, and seeing themselves as empowered actors in their own lives, people might turn those happenstances into meaningful experiences that give them direction. In short, the findings of the current study not only confirmed the effects of the previous career intervention studies (Thomas & McDaniel, 2004; Tinsley et al., 2002; Vernick et al., 2004; Wessel et al., 2003; Whiston et al., 2003), but also took a step toward laying the foundation for an effective career intervention course that acknowledges and would help persons to cope with the challenges of 21st-century career development.
CONCLUSION AND RECOMMENDATIONS
Chance plays a significant role in peoples lives; however, by consciously influencing their thinking and affective states through metacognitive strategies, people can turn chance events into planned happenstances that become meaningful rather than unavoidable occurrences. In our modern technological world, a career approach synthesizing both concepts may produce a powerful and viable alternative to more traditional career counseling approaches. The current research provided evidence that a career training course combining metacognitive and planned happenstance perspectives could significantly improve students' self-concept, motivation, time management, and ability to solve learning problems. Furthermore, these improvements were accompanied by behavior changes. Students who have undergone such training may be better equipped to handle the rapid changes that will occur during their careers. We recommend further research in this area using more diverse populations to validate the findings reported here. In addition, a true experimental design, in which participants are randomly selected and assigned to either a control or a treatment group (in contrast to this study's quasiexperimental use of a nonequivalent control group), would provide stronger evidence of the effectiveness of the metacognitive/planned happenstance approach.
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Ju-Chun Chien, Counseling Center, Oriental Institute of Technology, Taipei, Taiwan; Jerome M. Fischer, Counseling and School Psychology, and Ernest Biller, Career Counseling, Adult, Career, and Technology Education, University of Idaho. Correspondence concerning this article should be addressed to Jerome M. Fischer, Counseling and School Psychology, CASPEL-3083, University of Idaho, Moscow, ID 83844-3083 (e-mail: firstname.lastname@example.org).
TABLE 1 Analyses of Variance of Gain Scores of Four Groups on Five Measures Variable n F [[eta].sup.2] Tennessee Self-Concept Scale: Second Edition for Adults 144 4.21 ** .08 Learning and Study Strategies Inventory Motivation 152 4.39 ** .08 Time Management 152 3.95 * .07 Solving-Learning-Problems 152 3.59 * .07 The Metacognitive Competency Measure 139 8.89 ** .16 * p < .05. ** p < .01.
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|Author:||Chien, Ju-Chun; Fischer, Jerome M.; Biller, Ernest|
|Publication:||Journal of Employment Counseling|
|Date:||Dec 1, 2006|
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