The States and Biotechnology: Interests, Strategies, and Dimensions

John Portz and Peter Eisinger have provided a valuable conceptual overview of state government initiatives for economic development through biotechnology. Their three major models of policy choice - - based on interest-group processes, strategic planning, and competing interest groups in the allocation of planned development initiatives — seem to be sound theoretically and are convincingly examined empirically. Further, Portz and Eisinger provide a wealth of information regarding comparative state efforts at stimulating economic innovation, the differing state political dynamics underlying alternative development strategies, and differences in how such strategies have been implemented. Their analysis represents an important contribution to the current literature on comparative state economic development policy

3 reasons why people fall for politicians’ lies about statistics

Why do people make such poor decisions about politics? Why are they so often distracted by lies, irrelevant alternatives and specious arguments? Politicians use and abuse statistics and fabricate when it suits their purposes. Contemporary examples of either deliberate or inadvertent misuse of data are easy to find on all sides of the political divide, from the Trump administration’s claim that U.S. border officials detained “nearly 4,000 known or suspected terrorists” last year at the Mexican border to U.S. Rep. Alexandria Ocasio-Cortez’s December tweet asserting that “66 percent of Medicare for All could have been funded already” with the money spent on the Pentagon’s accounting errors

Academic Success for STEM and Non-STEM Majors

Enrollment in STEM majors has improved recently, but there continues to be concern over retention in those majors, especially of women and minority students. The purpose of this study is to develop an integrated understanding of how multiple predictor variables affect student degree attainment and to ascertain how the variables impact is regulated by whether students are in STEM or non-STEM majors. Six-year cohort retention/graduation outcomes are predicted for all students in STEM and non-STEM majors, and are adjusted separately for whether students remain in, or shift into or away from, STEM majors. Long-term retention/graduation is predicted significantly by cumulative grade point average, financial need, aid (work-study, loan, and gift), gender, ethnicity, years living on campus, high school rank (HSR), ACT composite, out-of-state residence, and STEM status. For students starting out in non-STEM majors, six-year graduation/retention also is predicted significantly by learning community participation and whether the student switches to a STEM major

Considering Students\u27 Perceptions: The Distance Education Student Satisfaction Model

In the current study, the Distance Education Student Satisfaction Model, estimated as a structural equation model, is proposed to understand better what predicts student satisfaction from online learning environments. In the present study, the following variables are employed based on the Technology Acceptance Model (TAM) (Davis, Bagozzi, & Warshaw, 1989) and literature: computer knowledge, flexibility of distance education, usefulness of distance education, and distance education satisfaction. Results suggest that as long as students have the skills to use online tools and perceive that distance education is a useful and flexible way of learning, communicating, and sharing, their enjoyment from online instruction will be promoted. Ultimately, this satisfaction may lead to higher levels of engagement, learning, and success in the distance education setting. Data collected from 195 undergraduate students are analyzed using Statistical Package for the Social Sciences and Analysis of Moment Structures statistical software. Implications of the findings of the present study are crucial for instructors, practitioners, and institutions planning to offer or currently engaged in offering distance education courses

External Factors Affecting Room and Board Rates: How Much Influence Does the Housing Director Have?

The cost of attending college is an issue that has appeared frequently in contemporary literature (Choy & Premo, 1996; Stringer, Cunningham, Merisotist Wellman, & O\u27Brien, 1999; The Institute for Higher Education Policy, The Ford Foundation, & The Education Resources Institute, 1999). College costs have increased faster than median family income (Stringer, Cunningham, O\u27Brien, & Merisotis, 1998), and many students and their parents have underestimated the actual cost of attendance. An important element in determining the total cost of attendance is the amount students pay for room and board if they choose to live on-campus. Many experts recommend an on-campus living experience as a way to enrich a student\u27s education (KUh, Douglas, Lund, & Ramin Gyurnek, 1994; Pascarella & Terenzini, 1991 ; Schuh, 1999)

Analysis of the Relationship between University Students’ Problematic Internet Use and Loneliness

: The computer is part of the information and communication age, and the Internet today is the most used communication tool. Studies have shown that there is a relationship between problematic Internet use and loneliness. The aim of this study was to investigate the relationship between problematic Internet use sub-scales and loneliness. In this study, data were collected from the college students at an Anatolian University in Turkey. The participants of this study consisted of 392 undergraduates. Of the participants, 43% are male (n = 167) and 57% female (n = 225). The average age for the participants is 22 years old. The Problematic Internet Use Scale and the University of California, Los Angeles (UCLA) Loneliness Scale were used as data collection instruments. In the present study, structural equation modeling (SEM) procedures are used to explore the relationships that exist among the variables. The findings of the study revealed that while university students’ social benefit/social comfort of Internet has a direct effect on their excessive Internet use and negative consequences, it is related to the loneliness level indirectly. In addition, it is seen in the research model that with an increase in the negative consequences of the Internet, the loneliness level was raised. Another result from the study is that when university students’ excessive Internet use increased, their loneliness level decreased

Transfer of Learning in Mathematics, Science, and Reading among Students in Turkey: A Study Using 2009 PISA Data

Using Program for International Student Achievement (PISA) 2009 data we study the transfer of knowledge among reading, mathematics, and science among Turkish students. Both Science and Reading are significant predictors of Mathematics scores, although clearly Science is a much stronger predictor; the transfer from Science to Mathematics is much greater than is the transfer from Reading to Mathematics. SCHOOLID is the single strongest predictor of Mathematics outcomes, likely reflecting the importance of socioeconomic and regional or urban/rural differences in the quality of education available to students. Both Mathematics and Reading are significant predictors of Science scores, although Mathematics is a stronger predictor; the transfer from Mathematics to Science is greater than is the transfer from Reading to Science. SCHOOLID is a weaker predictor of Science outcomes than are Mathematics scores, suggesting that the importance of socioeconomic and regional or urban/rural differences in the quality of education available to students may have slightly less consequence for Science outcomes than does the transfer effect from Mathematics to Science. Both Science and Mathematics are significant predictors of Reading scores, but the transfer from Science to Reading is much more robust than the transfer from Mathematics to Reading. SCHOOLID and Science are nearly identically strong predictors of Reading outcomes, suggesting that the importance of socioeconomic and regional or urban/rural differences in the quality of education available is on a par with the Science transfer to Reading. Implications of these findings are discussed

A Structural Equation Model Correlating Success in Engineering with Academic Variables for Community College Transfer Students

Student Enrollment and Engagement through Connections is a collaboration between a large Midwestern university and in-state community colleges (CCs) to increase success of transfers into engineering. This study explores predictors of completing a BS in engineering for CC transfers through a structural equation model. The model was estimated using academic variables from both institutions. The dataset includes 472 in-state CC transfer students admitted to the College of Engineering between 2002 and 2005. The model fits the data well (χ2=74.254, df=30, p\u3c0.0001; RMSE=0.056, Comparative Fit Index=0.984, chi-square/df ratio=2.475). First spring University GPA and credit hours, CC transfer credits toward core engineering courses, first fall credit hours after transfer, first fall University GPA, and University core course GPA are significantly related to graduation in engineering. This research may help increase the success of CC transfers to engineering, emphasizing the importance of core engineering courses

Structural Analysis of Factors Influencing the Adjustment Behaviors of Korean Children in the U.S.

The purpose of this study was to identify factors influencing the adjustment of Korean children who live in the U.S. Specifically, this study examined the following predictor variables: English proficiency, peer relationships, family relationships, and school experiences. Forty seven Korean children who were attending the Korean Lan-guage School and their parents participated in this study. Pearson product moment correlations indicated that there was a statistically significant relationship between the adjustment of Korean children who live in the U.S. and their English proficiency, peer relationships, and school experiences. There was no statistically significant relationship between the adjustment of Korean children who live in the U.S. and their family relationships. Ad-ditionally, structural equation modeling (SEM) was examined to explore how English proficiency, family rela-tionships, peer relationships, and school experiences may serve as influential factors for adjustment of Korean children who live in the U.S. The resulting model had a good fit, χ2 = 2.02, χ2/df = 1.01, comparative fit index (CFI) = 1.00, root mean square error of approximation (RMSEA) = 0.02, which is small enough to indicate a good fit, and indicated that Korean children’s school experiences had the strongest relationship with their overall adjustment score (β = .73, p \u3c .001). However, the effects of English proficiency and family relationships on adjustment were mediated through school experiences, although it is important to note that English proficiency did not have a positive relationship with school experience (β = -.38, p = .340), but Korean children’s school experiences were positively associated with their English proficiency (β = .68, p \u3c .05)

Contributors to Residence Hall Student Retention: Why do Students Choose to Leave or Stay?

Residence hall occupancy is of concern to housing administrators because higher occupancy leads to financial stability. While many areas are housing more students, some regions such as the Midwest are experiencing enrollment declines primarily due to a decline in high-school graduates and a struggling economy (Meline, 2003). In the Midwest there are daily newspaper reports of declining enrollment, budget cuts, reduction in financial resources, and increased competition for government funding and private support. When occupancy is low, it is especially desirable for housing administrators to learn more about what motivates students in their choice of housing