Counseling Self-Efficacy and the Relational Efficacy Model

Relation-inferred self-efficacy (RISE), a relatively new concept, is defined as a target individual’s beliefs about how an observer, often a relationship partner, perceives the target’s ability to perform certain actions successfully. Along with self-efficacy (i.e., one’s beliefs about his or her own ability) and other-efficacy (i.e., one’s beliefs about his or her partner’s ability), RISE makes up a three part system of interrelated efficacy beliefs known as the relational efficacy model (Lent & Lopez, 2002). Previous research has shown this model to be helpful in understanding how relational dyads, including coach-athlete, advisor-advisee, and romantic partners, contribute to the development of self-efficacy beliefs. The clinical supervision dyad (i.e., supervisor-supervisee), is another context in which relational efficacy beliefs may play an important role. This study investigated the relationship between counseling self-efficacy, RISE, and other-efficacy within the context of clinical supervision. Specifically, it examined whether supervisee perceptions about how their supervisor sees their counseling ability (RISE) related to how supervisees see their own counseling ability (counseling self-efficacy), and what moderates this relationship. The study also sought to discover the degree to which RISE mediated the relationship between supervisor working alliance and counseling self-efficacy. Data were collected from 240 graduate students who were currently enrolled in counseling related fields, working with at least one client, and receiving regular supervision. Results demonstrated that years of experience and RISE predicted counseling self-efficacy and that the relationship between RISE and counseling self-efficacy was, as expected, moderated by other-efficacy. Contrary to expectations, however, counseling experience and level of client difficulty did not moderate the relationship between RISE and counseling self-efficacy. These findings suggest that the relationship between RISE and counseling self-efficacy was stronger when supervisees saw their supervisors as capable therapists. Furthermore, RISE was found to fully mediate the relationship between supervisor working alliance and counseling self-efficacy. Future research directions and implications for training and supervision are discussed.

FRAMEWORK SYNTHESIS FOR SYMBOLIC EXECUTION OF EVENT-DRIVEN FRAMEWORKS

Symbolic execution is a powerful program analysis technique, but it is very challenging to apply to programs built using event-driven frameworks, such as Android. The main reason is that the framework code itself is too complex to symbolically execute. The standard solution is to manually create a framework model that is simpler and more amenable to symbolic execution. However, developing and maintaining such a model by hand is difficult and error-prone. We claim that we can leverage program synthesis to introduce a high-degree of automation to the process of framework modeling. To support this thesis, we present three pieces of work. First, we introduced SymDroid, a symbolic executor for Android. While Android apps are written in Java, they are compiled to Dalvik bytecode format. Instead of analyzing an app’s Java source, which may not be available, or decompiling from Dalvik back to Java, which requires significant engineering effort and introduces yet another source of potential bugs in an analysis, SymDroid works directly on Dalvik bytecode. Second, we introduced Pasket, a new system that takes a first step toward automatically generating Java framework models to support symbolic execution. Pasket takes as input the framework API and tutorial programs that exercise the framework. From these artifacts and Pasket's internal knowledge of design patterns, Pasket synthesizes an executable framework model by instantiating design patterns, such that the behavior of a synthesized model on the tutorial programs matches that of the original framework. Lastly, in order to scale program synthesis to framework models, we devised adaptive concretization, a novel program synthesis algorithm that combines the best of the two major synthesis strategies: symbolic search, i.e., using SAT or SMT solvers, and explicit search, e.g., stochastic enumeration of possible solutions. Adaptive concretization parallelizes multiple sub-synthesis problems by partially concretizing highly influential unknowns in the original synthesis problem. Thanks to adaptive concretization, Pasket can generate a large-scale model, e.g., thousands lines of code. In addition, we have used an Android model synthesized by Pasket and found that the model is sufficient to allow SymDroid to execute a range of apps.

SEEKING CULTURAL FAIRNESS IN A MEASURE OF RELATIONAL REASONING

Relational reasoning, or the ability to identify meaningful patterns within any stream of information, is a fundamental cognitive ability associated with academic success across a variety of domains of learning and levels of schooling. However, the measurement of this construct has been historically problematic. For example, while the construct is typically described as multidimensional—including the identification of multiple types of higher-order patterns—it is most often measured in terms of a single type of pattern: analogy. For that reason, the Test of Relational Reasoning (TORR) was conceived and developed to include three other types of patterns that appear to be meaningful in the educational context: anomaly, antinomy, and antithesis. Moreover, as a way to focus on fluid relational reasoning ability, the TORR was developed to include, except for the directions, entirely visuo-spatial stimuli, which were designed to be as novel as possible for the participant. By focusing on fluid intellectual processing, the TORR was also developed to be fairly administered to undergraduate students—regardless of the particular gender, language, and ethnic groups they belong to. However, although some psychometric investigations of the TORR have been conducted, its actual fairness across those demographic groups has yet to be empirically demonstrated. Therefore, a systematic investigation of differential-item-functioning (DIF) across demographic groups on TORR items was conducted. A large (N = 1,379) sample, representative of the University of Maryland on key demographic variables, was collected, and the resulting data was analyzed using a multi-group, multidimensional item-response theory model comparison procedure. Using this procedure, no significant DIF was found on any of the TORR items across any of the demographic groups of interest. This null finding is interpreted as evidence of the cultural-fairness of the TORR, and potential test-development choices that may have contributed to that cultural-fairness are discussed. For example, the choice to make the TORR an untimed measure, to use novel stimuli, and to avoid stereotype threat in test administration, may have contributed to its cultural-fairness. Future steps for psychometric research on the TORR, and substantive research utilizing the TORR, are also presented and discussed.