Examining the guidelines for assessment and instruction in statistics education in relation to teaching styles priorities in introductory statistics courses.

The American Statistical Association (2005) describes a need to reexamine and review many introductory statistics courses to help achieve the important learning goals for students (p. 10). The goal of introductory statistics courses is to produce students who are statistically educated. Statistics educators for many years have been concerned with reforming the introductory course in statistics, a non-calculus based, often terminal, introductory applied statistics course (Garfield, 2000, p. 2). The Guidelines for Assessment and Instruction in Statistics Education (GAISE) are six recommendations that have evolved out of this need for reform. These recommendations have the intent to help students attain learning goals that are appropriate for an introductory statistics course. The six recommendations are emphasize statistical literacy and develop statistical thinking, use real data, stress conceptual understanding rather than mere knowledge of procedures, foster active learning in the classroom, use technology for developing conceptual understanding and analyzing data, and use assessment to improve and evaluate student learning. Using Q methodology (principal components analysis and varimax rotation) to capture opinions of teachers of introductory statistics toward their teaching styles priorities, this study used 44 statements reflecting the GAISE recommendations for 21 teachers of introductory statistics to sort. Analysis resulted in two viewpoints of teaching preferences: (a) Conceptual Teachers and (b) Applied Teachers. The Conceptual Teacher’s typology represents those who focus on teaching the concepts to students using passive learning techniques (note taking, lack of hands-on activities), but expect students to be able to make appropriate decisions when using statistics. The Applied Teacher’s typology represents those who focus on teaching the fundamentals of statistics to students using active learning techniques (activities, discussion, examples), but do not expect students to be able to make appropriate decisions yet when using statistics. A discussion of which GAISE recommendations are salient in each viewpoint is presented

Evaluation of a Child Abuse Prevention Home Visitation Program Using Predictive Discriminant Analysis to Identify Reasons for Early Departure

A formative evaluation of a state sponsored child abuse prevention program that focuses on first time mothers who are past their 29th week of pregnancy. The goals of the program are to improve the primary caregiver’s health, improve the health and development of the child, to enhance family functioning and stability, to teach positive parenting techniques, and to teach safety practices to all family members. The purpose of this evaluation is to identify variables that differentiate clients who complete the program from those who do not continue in the program past the child’s third birthday. A predictive discriminant analysis was used to analyze archival data for trends regarding reasons for leaving the program early and to develop a model for future prediction. Predictive models can then be applied to identify future clients’ propensity to complete the program and make appropriate changes in program implementation to encourage long-term program involvement

Death-primed memory suppression.

Participants (17 males, 37 females) performed a computer-based, five-phase, study recall-suppress-test-recognize task. Participants significantly suppressed more nonword target items compared to death-related prime-target pairs, and with more suppression confidence

Predicting community college transfer student success: The role of community college academic experiences on post-transfer adjustment

Community college students who transfer to four-year universities face a variety of academic, social, and psychological challenges as they adjust to new postsecondary institutions (Laanan, 2001; Townsend, 2008). Student success through the transfer process is positively influenced by accumulated knowledge, skills, and experiences from the community college environment, characterized as transfer student capital (Laanan, Starobin, and Eggleston, 2011; Moser, 2012). Because community college students are less likely to interact with their institutions through structured out-of-classroom living-learning communities, it is especially important to examine the role of classroom experiences on educational outcomes for this population (Tinto, 2000). The purpose of this study was to examine the impact of academic experiences in the classroom and with community college faculty members on transfer student outcomes at four-year universities, specifically self-efficacy/intent to persist and academic adjustment. A hypothesized structural model of academic forms of transfer student capital and their relationship with self-efficacy/intent to persist was tested using Laanan-Transfer Student Questionnaire (L-TSQ) data from community college transfer students at two public universities in the Midwest. The results of this study provide insight about the influence of specific forms of student-faculty interaction and classroom experiences on academic adjustment at four-year universities. The associated implications for research, policy, and practice presented in this study provide information that will help community college and university educators and policy makers to promote successful completion for increasing numbers of community college transfer students

The Use of Digital Technology in Extension

This Commentary describes how andragogy has evolved with the emergence of digital technology. The information can be used by Extension educators to merge technology with traditional adult education theory. Knowles\u27 assumptions of adult learners are discussed as they relate to an online learning environment. The role of Extension educators as facilitators of self-directed learning via the Internet is of specific interest to field specialists

Course-Embedded Peer Mentor Program

The involvement of peer leaders has been a key feature of First-Year Cornerstone since early in its development, reflecting the value placed on collaboration between students, faculty members, and student affairs staff from the beginning of the Foundations of Excellence process. Early on, we envisioned course-embedded peers as teaching assistants who would collaborate with Cornerstone faculty members on classroom activities and provide academic assistance to first-year students. After the first two years of the program, it was clear that students viewed their peer teaching assistants (PTAs) as helpful, approachable guides through their transition to college. While academic support was one element of PTA engagement with students, we soon realized that the mentoring and relationship-building aspect of their work was most valued by students, and often contributed to the development of classroom communities characterized by support, friendship, and peer accountability. This shift in emphasis led to a name change, from peer teaching assistants to peer mentors

A method to computationally screen for tunable properties of crystalline alloys

Conventionally, high-throughput computational materials searches start from an input set of bulk compounds extracted from material databases, and this set is screened for candidate materials for specific applications. In contrast, many functional materials, and especially semiconductors, are heavily engineered alloys or solid solutions of multiple compounds rather than a single bulk compound. To improve our ability to design functional materials, in this work we propose a framework and open-source code to automatically construct possible "alloy pairs" and "alloy systems" and detect "alloy members" from a set of existing, experimental or calculated ordered compounds, without requiring any additional metadata beyond their crystal structure. We provide analysis tools to estimate stability across each alloy. As a demonstration, we apply this framework to all inorganic materials in the Materials Project database to create a new database of over 600,000 unique alloy pair entries that can then be used in materials discovery studies to search for materials with tunable properties. This new database has been incorporated into the Materials Project website and linked with corresponding material identifiers for any user to query and explore. Using an example of screening for p-type transparent conducting materials, we demonstrate how using this methodology reveals candidate material systems that might otherwise have been excluded by a traditional screening. This work lays a foundation from which materials databases can go beyond stoichiometric compounds, and approach a more realistic description of compositionally tunable materials

Conjoint Analysis of Breaded Catfish Nuggets: Consumer Preferences for Price, Product Color, Cooking Method and Country of Origin

A new product, marinated, breaded catfish nuggets, was developed. This conjoint study was designed to evaluate consumers’ preferences for certain attributes of the nuggets. An in-store survey was conducted to collect data. The data collected will be used to determine the market potential for the catfish nuggets.Food Consumption/Nutrition/Food Safety,

How does the preference for increasing payments depend on the size and source of the payments?

It is well-known that subjects can exhibit a preference for increasing payments. Smith (2009a) makes a related prediction that the difference between the preference increasing wage payments and the preference for increasing non-wage payments will be largest for intermediate payments. We find evidence consistent with this prediction. Consistent with previous experiments, we find that the preference for increasing payments is increasing in the size of the payments. Also consistent with the literature, we find that the preference for increasing wage payments is stronger than the preference for non-wage payments