This 3-year longitudinal study tested and extended Sénéchal and Le Fevre's (2002) model of the relationships between preschool home literacy practices and children's literacy and language development. Parent-child reading (home literacy environment questionnaire plus children's Title Recognition Test) and parental teaching of letters, words and name writing were assessed 6 months prior to children's school entry. The 143 children (55% males; mean age 5.36 years, SD = 0.29) attended Gold Coast, Australia government Preschools. Parent-child reading and literacy teaching were only weakly correlated (r = .18), and were related to different outcomes consistent with the original model. Age, gender, memory, and non-verbal ability were controlled. Parental teaching was independently related to Preschool Woodcock Letter-Word Identification scores (R 2 change = 4.58%, p = .008). This relationship then mediated the relationships between parental teaching and Grade 1 and 2 letter-word identification, single-word reading and spelling rates, and phonological awareness (rhyme detection and phonological deletion). Parent-child reading was independently related to Grade 1 vocabulary (R 2 change = 5.6%, p =.005). Thus, both home practices are relevant, but to different aspects of literacy and language development.

We surveyed 245 first-year university students using measures of career concerns, career adaptability (career planning, career exploration, self exploration, decision-making, selfregulation), goal-orientation (learning, performance-prove, performance-avoid) and social support (family, friends, significant others), and tested: (a) whether the career adaptability variables could be represented by a second-order factor of career adaptability; (b) whether career adaptability, goal-orientation and social support were associated with fewer career concerns; and (c) whether career adaptability mediated the relationship between goal-orientation and social support and career concerns. The study demonstrated that the career adaptability variables were interrelated and could be represented by a higher-order factor. Decision-making and self-exploration were negatively associated with career concerns, and decision-making mediated the relationship between goal-orientation and career concerns. Having more of a learning orientation was associated with more decision-making and fewer career concerns, whereas holding a performance-prove orientation was associated with poorer decision-making and more career concerns.

Theory-based longitudinal research on career calling is sparse. In a two-wave, cross-lagged panel design we assessed Hall and Chandler's (2005) calling model of psychological career success using 216 young adults (M age = 20.44 years, SD = 2.54). We tested if changes in career calling over time were associated with changes in goal-directed effort (work effort and career strategies) and psychological career success (life meaning and career adaptability) over time, and if goal-directed effort mediated between career calling and psychological career success over time. The standard causal model showed a better fit over the base, reverse, and reciprocal causation models. T1 career calling predicted T2 work effort, career strategies, life meaning, and career adaptability. Only career strategies mediated between T1 career calling and T2 life meaning and T2 career adaptability. Limitations and future directions are discussed.

Career calling, a salient career goal that is personally meaningful and oriented toward helping others, is a developmental construct that is especially important for emerging adults when making career decisions and setting career goals. As no existing measure reflects the developmental aspect of career calling, we devised an age-appropriate measure suitable for use with this population. We reviewed the extant literature, conducted focus groups, and used expert reviews to generate 34 initial items. Item and exploratory factor analyses were employed to reduce these items to 15, representing three reliable subscales (Study 1; N ¼ 345 emerging adults). Confirmatory factor analysis supported the initial factor structure (Study 2; N ¼ 527). Expected correlations with adult measures of career calling (search and presence), general career indecision, and life satisfaction supported construct validity (Study 2; N ¼ 435). The implications for research and practice are discussed.

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We tested a mediation model of career calling, in which career calling was associated positively with life satisfaction and perceptions of future employability, and these relationships were explained by the self-regulatory mechanisms of work effort, career strategies, and emotional regulation. Using a sample of 664 emerging adults (74.8% female, mean age = 20.2 years), we found that higher career calling was associated with better life satisfaction and more positive perceived employability, that higher career calling was associated with more work effort, more use of career strategies, and better emotional regulation, and that the self-regulatory strategies mediated between career calling and life satisfaction (work effort and emotional regulation) and between career calling and perceived employability (work effort, emotional regulation, and career strategies). We interpreted the results from a developmental and goal-setting perspective, and made recommendations for practice.

BackgroundSimulation based learning environments are designed to improve the quality of medical education by allowing students to interact with patients, diagnostic laboratory procedures, and patient data in a virtual environment. However, few studies have evaluated whether simulation based learning environments increase students’ knowledge, intrinsic motivation, and self-efficacy, and help them generalize from laboratory analyses to clinical practice and health decision-making.MethodsAn entire class of 300 University of Copenhagen first-year undergraduate students, most with a major in medicine, received a 2-h training session in a simulation based learning environment. The main outcomes were pre- to post- changes in knowledge, intrinsic motivation, and self-efficacy, together with post-intervention evaluation of the effect of the simulation on student understanding of everyday clinical practice were demonstrated.ResultsKnowledge (Cohen’s d = 0.73), intrinsic motivation (d = 0.24), and self-efficacy (d = 0.46) significantly increased from the pre- to post-test. Low knowledge students showed the greatest increases in knowledge (d = 3.35) and self-efficacy (d = 0.61), but a non-significant increase in intrinsic motivation (d = 0.22). The medium and high knowledge students showed significant increases in knowledge (d = 1.45 and 0.36, respectively), motivation (d = 0.22 and 0.31), and self-efficacy (d = 0.36 and 0.52, respectively). Additionally, 90 % of students reported a greater understanding of medical genetics, 82 % thought that medical genetics was more interesting, 93 % indicated that they were more interested and motivated, and had gained confidence by having experienced working on a case story that resembled the real working situation of a doctor, and 78 % indicated that they would feel more confident counseling a patient after the simulation.ConclusionsThe simulation based learning environment increased students’ learning, intrinsic motivation, and self-efficacy (although the strength of these effects differed depending on their pre-test knowledge), and increased the perceived relevance of medical educational activities. The results suggest that simulations can help future generations of doctors transfer new understanding of disease mechanisms gained in virtual laboratory settings into everyday clinical practice.Electronic supplementary materialThe online version of this article (doi:10.1186/s12909-016-0620-6) contains supplementary material, which is available to authorized users.

At Time 1 (T1), the authors surveyed 277 unemployed adults using measures of human capital, goal orientation, self-regulation (emotion control, motivation control, work commitment), and job-seeking intensity. At Time 2 (T2), 4 months later, 155 participants indicated their reemployment outcomes in number of job interviews and number of job offers. Using T1 data, the authors tested the predictors of job-seeking intensity and whether self-regulation mediated between goal orientation and job-seeking intensity. Using T1 and T2 data, they tested for predictors of reemployment outcomes and whether job-seeking intensity mediated the relationship between T1 antecedent variables and the reemployment outcomes. Learning goal orientation and self-regulation predicted job-seeking intensity, and self-regulation mediated between learning goal orientation and job-seeking intensity. Job-seeking intensity did not mediate the relationship among human capital, goal orientation, and self-regulation variables and reemployment outcomes.