Principles and Practice of Structural Equation Modeling (2nd ed.)

Summary The foregoing review of the career barriers literaturepresents a mixed picture. On the one hand, students andworkers do perceive barriers to their career progress; but onthe other hand, barrier ratings are often found to besomewhat modest in size and have not been shown to beconsistently related to important career outcome or processvariables in the mostly student samples in which they havebeen studied. This is not to say that barriers are notconsequential for many Individuals. Indeed, they are likelyto be especially salient for those who have been victimizedby various forms of oppression. However, several concep-tual and methodological issues—such as the manner inwhich barriers have been defined, failure to consider thecontext and temporal specificity of barriers, noncorrespon-dence between barriers and outcome criteria (in terms ofcontent and developmental task), infrequent attention tomediating and moderating variables, understudy of nonstu-dent samples, and use of designs that do not explorepotential causal effects of barriers—may have partly ob-scured the impact of perceived barriers and the mechanismsthrough which they affect career behavior.Despite these considerations, recent career barriers re-search has constructed an important conceptual and method-ological foundation for further inquiry, and the program-matic research of Swanson, McWhirter, and Luzzo and theircolleagues has been particularly pivotal. In the remainder ofthis article, we attempt to build on this foundation, offering amodest set of suggestions for future research on careerbarriers and their conceptual partner, career supports. Thesesuggestions are premised on the need to clarify or elaboratecertain aspects of SCCT having relevance for the conceptu-alization and assessment of contextual variables.

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Contextual supports and barriers to career choice: A social cognitive analysis.

Based on a developmental contextual perspective advocated by Vondracek, Lerner, and Schulenberg, this article provides a comprehensive review of the research published since 1980related to family of origin influences on career developmentandoccupational choice. Because individuals are most likely to seek assistance with career decisions from family members, it is important that counseling psychologists understand how families can have a positive influence and facilitate career development. Influential family contextual factors are identified within four developmentallevels (i.e., children, adolescents, college students/young adults, and adults). Across the lifespan, both family structure variables (e.g., parents’ occupations) and family process variables (e.g., warmth, support, attachment, autonomy) were found to influence a host of career constructs; however, the process by which families influence career development is complex and is affected by many contextual factors such as race, gender, and age. Bas...

The Influences of the Family of Origin on Career Development A Review and Analysis

Social cognitive career theory (SCCT; R. w. Lent, S. D. Brown, & G. Hackett, 1994) and general social cognitive theory (Bandura, 1999, 2000) posit somewhat different relations between contextual variables and choice actions. The authors tested the predictions of these 2 model variations. Participants (328 students in an introductory engineering course) completed measures of SCCT's person (self-efficacy, coping efficacy, outcome expectations, interests, academic goals) and contextual variables (environmental supports and barriers) related to the pursuit of engineering majors. Findings indicated good support for a model portraying contextual supports and barriers as linked to choice goals and actions (i.e., persistence in engineering) indirectly, through self-efficacy, rather than directly, as posited by SCCT. Implications for future research on SCCT's choice and environmental hypotheses are discussed.

http://psycnet.apa.org/journals/cou/50/4/458.pdf

Relation of Contextual Supports and Barriers to Choice Behavior in Engineering Majors: Test of Alternative Social Cognitive Models.

Social cognitive career theory proposes that contextual supports and barriers play key roles in the career choice process, yet little research has examined hypotheses involving these variables. Participants (111 1 college students) completed measures of math/science-related course self-efficacy, coping efficacy, outcome expectations, interests, goals, and perceived contextual supports and barriers. Findings indicate that self-efficacy and outcome expectations were jointly predictive of interests and choice intentions. Support and barrier percepts produced only weak direct relations to choice, though barrier percepts were found to moderate interest-choice relations. A model portraying barriers and supports as linked to choice indirectly (via their impact on self-efficacy) produced better fit to the data than did a model specifying barriers and supports as directly linked to choice. Implications for future research and counseling are discussed.

The role of contextual supports and barriers in the choice of math/science educational options: A test of social cognitive hypotheses

Asian Americans' career choices: A path model to examine factors influencing their career choices.

This article explores the factors influencing high school students' career aspirations with a study analyzing 141 high school students. The Social Cognitive Career Development Model was utilized to examine the interactive relationships among learning experiences, career self-efficacy, outcome expectations, career interests, and career choices. The results of a structural equation modeling analysis supported the mediating role of career self-efficacy in the career decision-making process, but the specific paths among the predicting variables to career aspirations were found to be different for female and male high school students. Implications for school counselors to provide more effective career intervention programs are discussed.

Factors Influencing High School Students' Career Aspirations.

Statistics anxiety is prevalent among students whose academic background has little statistical training. The development and psychometric properties of statistics anxiety scales and the factors affecting statistics anxiety have been extensively studied for more than twenty years, but few studies focused on how to reduce the statistics anxiety for graduate students in the social sciences. The present study explores how statistics anxiety can be reduced by various innovative instructional methods. A repeated measures ANCOVA with controlling for individual differences is utilized to analyze a sample data from 21 social science graduate students at a Midwest university. The study shows that the combining application-oriented teaching methods with instructors' attentiveness to students' anxiety is a significantly effective way (p KEY WORDS: Statistics anxiety: Statistics education; Learning statistics; Teaching statistics; Innovative instructional methods; Teaching strategy ********** Many graduate students in the social sciences need to take statistics as part of the academic training, but these students often do not necessarily have backgrounds in statistics or mathematics from their undergraduate degree or other graduate training. In the classrooms, statistics anxiety is noticeably prevalent among graduate students whose academic background has little statistical training. According to Onwuegbuzie. Slate, Paterson, Watson, and Schwartz (2000), 75% to 80% of graduate students appear to experience uncomfortable levels of statistics anxiety. As a result, conducting statistics is often rated as the lowest skill in terms of academic competence (Huntley, Schneider, and Aronson, 2000). Statistics anxiety has been defined simply as anxiety that occurs as a result of encountering statistics in any form and at any level (Onwuegbuzie, DaRos, & Ryan, 1997), and has been found to negatively affect learning (Onwuegbuzie & Seaman, 1995). Many researchers (Lazar, 1990; Lalonde & Gardner, 1993; Onwuegbuzie, 2000b) suggested that learning statistics is as difficult as learning a foreign language. On the other hand, statistics anxiety sometimes is not necessarily due to the lack of training or insufficient skills, but due to the misperception about statistics and negative experiences in a statistical class. For instance, students often think they do not have enough mathematics training so that they cannot do well in statistical classes. With fear of failing the course, they delay enrolling in statistics courses as long as possible, which often leads to failure to complete their degree programs (Onwuegbuzie, 1997). The lack of self-efficacy and higher anxiety in statistics keep many students away from engaging in research work or further to pursue an academic career. Therefore, statistics becomes one of the most anxiety-inducing courses in their programs of study (Blalock, 1987; Caine, Centa, Doroff, Horowitz, & Wisenbaker, 1978; Schacht & Stewart, 1990; Zeidner, 1991). In the literature, statistics anxiety has been extensively studied for more than two decades. The majority of the studies have focused primarily on measurement of and factors contributing to statistics anxiety. The development of statistics anxiety instruments was derived from mathematics anxiety assessment. For example, the Statistical Anxiety Scale (Pretorius & Norman, 1992) was developed by replacing the word "mathematics" with the word "statistics" in some items of the Mathematics Anxiety Scale (Fennema & Sherman, 1976; Betz, 1978). The reliability and factor analysis results showed good psychometric properties of the Statistics Anxiety Scale. In 1991, Zeidner replaced the word "mathematics" with the word "statistics" in a 40-item version of the Mathematics Anxiety Rating Scale (Richard & Woolfolk, 1980) and developed the Statistics Anxiety Inventory. …

Examining the Effectiveness of Innovative Instructional Methods on Reducing Statistics Anxiety for Graduate Students in the Social Sciences.

We explored students" experiences in a statistics class to investigate what factors contributed to students' anxiety and how instructional strategies helped students learn statistics effectively. The participants were graduate students in the social sciences at a large Midwest university. The findings from the study demonstrate that factors contributing to statistics anxiety include math phobia, lack of connection to daily life, pace of instruction, and instructor's attitude. The results also show that using multidimensional instructional methods and instructor's being attentive to students' anxiety are helpful strategies to reduce students' anxiety. Key words: statistics anxiety, learning statistics, teaching statistics ********** Statistics anxiety is defined as anxiety that occurs as a result of encountering statistics in any form and at any level (Onwuegbuzie, DaRos, & Ryan 1997). In classrooms, statistics anxiety is noticeably common among students whose academic background includes little previous statistical or mathematical training. Onwuegbuzie, Slate, et al. (2000) stated that 75% to 80% of graduate students in the social sciences appeared to experience uncomfortable levels of statistics anxiety which negatively affected learning (Onwuegbuzie & Seaman 1995). Consequently, statistical analysis became the lowest academic skill for graduate students in the social sciences (Huntley, Schneider, & Aronson 2000). The dilemma is that almost all graduate students in the social sciences need to take statistics as part of their academic training. How training programs should help graduate students address statistics anxiety and help them learn statistics more effectively is important. Statistics anxiety is not only due to the lack of training or to insufficient skills, but is also due to misperception about statistics and negative experiences in previous statistics classes. For instance, students often think they do not have enough mathematics training to do well in statistics classes. The fear of failing the course causes a delay in enrolling in statistics courses for as long as possible, and the delay often leads to failure to complete degree programs (Onwuegbuzie 1997). The lack of self-efficacy and the high anxiety in statistics keep many students away from engaging in research work or furthering an academic career (Blalock 1987; Caine et al. 1978; Schacht & Stewart 1990; Zeidner 1991). The prevalence of statistics anxiety among graduate students in the social sciences has called for researchers' and educators' growing attention in the last decade. In the literature, statistics anxiety has been extensively studied in two major areas--measurement of and factors contributing to statistics anxiety. In the early stage, statistics anxiety instruments were derived from measurement of math anxiety, including the Statistical Anxiety Scale (Pretorius & Norman 1992) and the Statistics Anxiety Inventory (Richard & Woolfolk 1980). The Statistics Anxiety Rating Scale (STARS), developed by Cruise and Wilkins (1980) and Cruise, Cash, and Bolton (1985), is recently studied by Baloglu (2002) for its psychometric properties. More recently, Watson et al. (2003) incorporated the STARS along with a survey of attitude toward statistics into a multimedia program--EncStat (Encouraged About Statistics)--that aimed at identifying students with statistics anxiety or negative attitudes toward statistics. The factors contributing to students' anxiety are broad. Forte (1995) found several factors that were applicable to social work students who experienced statistics anxiety. These factors were minimal previous math preparation, late-in-career introduction to quantitative analysis, general anti-quantitative bias, lack of appropriation for the power of analytical models, and lack of mental imagery useful in thinking about quantitative concepts. Another investigation found that evaluation concern, fear of failure, and perfectionism were responsible for statistics anxiety (Walsh & Ugumba-Agwunobi 2002). …

Students' Perceptions on Factors of Statistics Anxiety and Instructional Strategies.

The literature on career development for people of Appalachian culture is sparse. This article reviews cultural values of Appalachians and proposes an innovative career intervention model to best serve people of this culture. The model integrates the concepts of the social cognitive career development approach (R. W. Lent, S. D. Brown, & G. Hackett, 1994) and ecological counseling principles (R. K. Conyne & E. P. Cook, 2004). As this model demonstrates, providing contextual and cultural accommodation is critical in order to gain the trust and permission to work with people of Appalachian culture. Research on career development of minority groups has been increasingly popular in the past 2 decades, but literature on people of Appalachian culture is more limited. Most of the literature focuses on the four major minority groups as identified in the multicultural textbooks: Asian Americans, Hispanic Americans, African Americans, and Native Americans. People of Appalachian culture have become an invisible minority because they do not appear outwardly different from mainstream Americans. This is particularly true of the "urban Appalachian" minority because they are encountered unexpectedly outside the area labeled Appalachia. Often considered as simply part of a lower socioeconomic group rather than as a cultural minority, people of Appalachian culture have their own distinct cultural values that differ from those of mainstream Americans. Appalachians Are defined as people born in the geographic area along the spine of the Appalachian Mountains, which include the Great Smoky Mountains and the Cumberland Mountains. The legal geographical boundaries were set by the Appalachian Regional Development Act of 1965 (ARDA; 1965) and include 406 counties in 13 states (all of West Virginia and parts of Alabama, Georgia, Kentucky, Maryland, Mississippi, New York, North Carolina, Ohio, Pennsylvania, South Carolina, Tennessee, and Virginia). ARDA created the Appalachian Regional Commission (ARC), which divided Appalachia into three subrogions: Northern (all Appalachian counties in Maryland, New York, Ohio, and Pennsylvania and some in Virginia and West Virginia), Central (all Appalachian counties in eastern Kentucky and some in Tennessee, Virginia, and West Virginia), and Southern (remaining Appalachian counties of Tennessee and Virginia, plus those in Alabama, Georgia, Mississippi, North Carolina, and South Carolina). Two thirds of the region is composed of rural counties (populations less than 10,000), with one third of the Appalachian population living in them, which is more than double the percentage of the rural population in all of the United States. Central Appalachia has the highest concentration of rural counties and the fewest urban ones. African Americans represent about 8% of the total population for people of Appalachian culture but a higher percentage (about 17%) of urban Appalachians (Maloney & Auffrey, 2004). Urban Appalachians, as referred to in this article and as titled by themselves (e.g., Urban Appalachian Council), are people of Appalachia who have migrated from the ARC region to cities outside Appalachia, not those living in cities within the ARC boundaries (Couto, 2002; Lewis, 2002; Obermiller & Howe, 2002). Estimates vary that from 2 to 5 million Black and White people of Appalachian culture migrated into midvvestern urban areas between 1940 and 1970, resulting in large subcultures in such cities as Detroit, Chicago, and Cincinnati (Berry, 2000; Borman & Obermiller, 1994; Hobbs, 1998; Iones, 2002; Wilson, 1983). The basic difference between people who remained in Appalachia and those who migrated to urban areas outside Appalachia was primarily home and/or land ownership, thus having an entrenched economic stake in thecommunity. Company ownership of workers' homes was one contributing factor to mobility. Share-cropping was another. There was no great demand for housing in most Appalachian areas during the 1940s to the 1970s, which made it difficult to convert what was often a family's soleasset to cash for moving expenses. …

Mei Tang

Papers

Asian Americans' career choices: A path model to examine factors influencing their career choices.

Factors Influencing High School Students' Career Aspirations.

Examining the Effectiveness of Innovative Instructional Methods on Reducing Statistics Anxiety for Graduate Students in the Social Sciences.

Students' Perceptions on Factors of Statistics Anxiety and Instructional Strategies.

Understanding and Facilitating Career Development of People of Appalachian Culture: An Integrated Approach