Standards-Based Evaluation and Teacher Career Satisfaction: A Structural Equation Modeling Analysis

Structural equation modeling was used to assess the plausibility of a conceptual model specifying hypothesized linkages among perceptions of characteristics of standards-based evaluation, work environment mediators, and career satisfaction and other outcomes. Four comprehensive high schools located in two neighboring counties in southern California provided the data for this study. The schools’ districts had recently developed and implemented evaluation systems based on six California Standards for the Teaching Profession generated in 1997. One hundred and seventy-eight teachers responded to survey questions designed to capture the following constructs: understandable/relevant standards, satisfactory/helpful evaluation, role ambiguity, effort performance-rating linkage, work criteria autonomy, career satisfaction, organizational commitment, and perceptions of the effectiveness of the evaluation system. Confirmatory factor analysis was used to assess whether the items measuring evaluation fit two hypothesized constructs. Structural equation modeling results indicated that there are two mediators in the evaluation-career satisfaction relationship: role ambiguity and work criteria autonomy.

Validation ROI: An HPT case study from the medical device industry

Validation is both a process and a function within Company ABC. Using the human performance technology (HPT) process, interventions were prescribed to address identified performance gaps. Forecasting an annual return on investment (ROI) based on goals yielded a ROI of 168%. Data collected for the first quarter of 2009 yielded a calculated ROI of 326%. This study discusses the HPT process and what was done to achieve the results.     

Advantages and Challenges of Using Physics Curricula as a Model for Reforming an Undergraduate Biology Course

We report on the development of a life sciences curriculum, targeted to undergraduate students, which was modeled after a commercially available physics curriculum and based on aspects of how people learn. Our paper describes the collaborative development process and necessary modifications required to apply a physics pedagogical model in a life sciences context. While some approaches were easily adapted, others provided significant challenges. Among these challenges were: representations of energy, introducing definitions, the placement of Scientists’ Ideas, and the replicability of data. In modifying the curriculum to address these challenges, we have come to see them as speaking to deeper differences between the disciplines, namely that introductory physics—for example, Newton''s laws, magnetism, light—is a science of pairwise interaction, while introductory biology—for example, photosynthesis, evolution, cycling of matter in ecosystems—is a science of linked processes, and we suggest that this is how the two disciplines are presented in introductory classes. We illustrate this tension through an analysis of our adaptations of the physics curriculum for instruction on the cycling of matter and energy; we show that modifications of the physics curriculum to address the biological framework promotes strong gains in student understanding of these topics, as evidenced by analysis of student work.     

Simulating conditions of learned helplessness: the effects of interventions and attributions

We report 2 experiments that assess factors potentially responsible for a proactive interference with the sensitivity of a mother's response to infant signals. Using a version of the "learned helplessness" paradigm, mothers' performance on a solvable task was assessed following pretreatments that involved exposure to an infant cry but that differed in the mothers' ability to exert control over the termination of the cry. Each experiment explored the role of varying attributions made by a mother in the development of, or the reversal of, the helplessness phenomenon. The first experiment addressed the question of whether a specific intervention (i.e., providing the mother an attribution for failure) can reduce the debilitating effect of prior experience with failure. The results indicated that the debilitating effects associated with previous failure were reversed for the 16 mothers assigned to the intervention group. 40 mothers participated in the second experiment, which varied attributions assigned to an identical cry stimulus (i.e., the cry was produced by an "easy" vs. a "difficult" infant). This experiment assessed the effect of varying attributions on the mothers' ability to terminate the cry. We found that mothers pretreated with inescapable cries and those receiving the experimental manipulation of attributing the cry to a "difficult" infant showed debilitated performance in stopping the cry when given the opportunity. We propose that models based on learned helplessness theory have value in the study of caregiver-infant relationships, in particular, caregivers' perceived and objective effectiveness in responding to an infant's signals.     

Using automated analysis to assess middle school students' competence with scientific argumentation

Argumentation is fundamental to science education, both as a prominent feature of scientific reasoning and as an effective mode of learning—a perspective reflected in contemporary frameworks and standards. The successful implementation of argumentation in school science, however, requires a paradigm shift in science assessment from the measurement of knowledge and understanding to the measurement of performance and knowledge in use. Performance tasks requiring argumentation must capture the many ways students can construct and evaluate arguments in science, yet such tasks are both expensive and resource-intensive to score. In this study we explore how machine learning text classification techniques can be applied to develop efficient, valid, and accurate constructed-response measures of students' competency with written scientific argumentation that are aligned with a validated argumentation learning progression. Data come from 933 middle school students in the San Francisco Bay Area and are based on three sets of argumentation items in three different science contexts. The findings demonstrate that we have been able to develop computer scoring models that can achieve substantial to almost perfect agreement between human-assigned and computer-predicted scores. Model performance was slightly weaker for harder items targeting higher levels of the learning progression, largely due to the linguistic complexity of these responses and the sparsity of higher-level responses in the training data set. Comparing the efficacy of different scoring approaches revealed that breaking down students' arguments into multiple components (e.g., the presence of an accurate claim or providing sufficient evidence), developing computer models for each component, and combining scores from these analytic components into a holistic score produced better results than holistic scoring approaches. However, this analytical approach was found to be differentially biased when scoring responses from English learners (EL) students as compared to responses from non-EL students on some items. Differences in the severity between human and computer scores for EL between these approaches are explored, and potential sources of bias in automated scoring are discussed.     

Programme evaluation toolbox: effective evaluation principles and considerations in career practice

In our ever-present age of accountability, career development professionals are increasingly called upon to document evidence-based outcomes and other metrics of programme effectiveness. In this article, we will review the key components of effective programme evaluation, including purposes and types of evaluation. Our review will span empirical and practical literature across disciplines and within guidance and counselling, specifically. We will review current evaluation models within an international context but focus predominantly on US based ones, along with articulating their shortfalls. Finally, we will present a potentially transformative advocacy-infused model of programme evaluation.     

Reading for meaning: The foundational knowledge every teacher of science should have

Reading is fundamental to science and not an adjunct to its practice. In other words, understanding the meaning of the various forms of written discourse employed in the creation, discussion, and communication of scientific knowledge is inherent to how science works. The language used in science, however, sets up a barrier, that in order to be overcome requires all students to have a clear understanding of the features of the multimodal informational texts employed in science and the strategies they can use to decode the scientific concepts communicated in informational texts. We argue that all teachers of science must develop a functional understanding of reading comprehension as part of their professional knowledge and skill. After describing our rationale for including knowledge about reading as a professional knowledge base every teacher of science should have, we outline the knowledge about language teachers must develop, the knowledge about the challenges that reading comprehension of science texts poses for students, and the knowledge about instructional strategies science teachers should know to support their students’ reading comprehension of science texts. Implications regarding the essential role that knowledge about reading should play in the preparation of science teachers are also discussed here.     

An elementary survey of the reading process

This article is a study of the social construction of school desegregation in Los Angeles, California. Particular emphasis is placed on how magnet schools were presented to area residents in the local press over a period of 3 decades. I use quantitative and qualitative techniques with 355 newspaper articles. I find that magnet schools were originally discussed as part of a larger desegregation program, but that references to desegregation declined steadily. Magnet schools are now discussed as providers of academic excellence, and desegregation issues are largely ignored. This follows the current trend in political and academic circles, in which the rhetoric surrounding education is increasingly focused on standards and accountability rather than equality and access.