Here’s My Thinking: A Quick Fix to Surface Student Reasoning

Supplemental Instruction (SI) is a learning enhancement program. SI targets high risk courses instead of high risk students and offers assistance on an outreach basis in regularly scheduled, out of class sessions. The primary goal of SI is to facilitate students' mastery of the course concepts, however a secondary goal is to encourage students to develop better learning skills and strategies. A student who has received a high grade in a targeted SI course is trained to become an SI leader. As an SI leader, the student re-attends the course to model effective student behaviors, and conducts weekly SI sessions. During the SI sessions, SI leaders facilitate students' understanding of course material via interactive learning strategies which encourage involvement, comprehension and higher order reasoning skills. SI leaders do not re-teach or simply work problems on the board; rather they offer alternative perspectives and exercises designed to mirror the course content. Penn State's SI program was piloted as a part of our larger Undergraduate Teaching Intern Program. The Teaching Intern (TI) Program allows undergraduate students to partner with a professor on a particular course in order to learn about the responsibilities of being a faculty member. This paper provides an overview of both the SI and TI programs, specific details on how to run a course to train for these programs, and preliminary results of the SI program in terms of experiences of the three student SI leaders and achievement results of those students who attended SI sessions versus those who did not.

Supplemental Instruction (SI) is a learning enhancement program. SI targets high risk courses instead of high risk students and offers assistance on an outreach basis in regularly scheduled, out of class sessions. The primary goal of SI is to facilitate students' mastery of the course concepts, however a secondary goal is to encourage students to develop better learning skills and strategies. A student who has received a high grade in a targeted SI course is trained to become an SI leader. As an SI leader, the student re-attends the course to model effective student behaviors, and conducts weekly SI sessions. During the SI sessions, SI leaders facilitate students' understanding of course material via interactive learning strategies which encourage involvement, comprehension and higher order reasoning skills. SI leaders do not re-teach or simply work problems on the board; rather they offer alternative perspectives and exercises designed to mirror the course content. Penn State's SI program was piloted as a part of our larger Undergraduate Teaching Intern Program. The Teaching Intern (TI) Program allows undergraduate students to partner with a professor on a particular course in order to learn about the responsibilities of being a faculty member. This paper provides an overview of both the SI and TI programs, specific details on how to run a course to train for these programs, and preliminary results of the SI program in terms of experiences of the three student SI leaders and achievement results of those students who attended SI sessions versus those who did not.

The objective of the research reported in this article was to evaluate the usefulness of supplemental videos in the advertising and public relations (PR) classroom, featuring luminaries in these same fields. Students in an introductory course in advertising and PR were given an assignment based on videos from an online library of short videos. Through a survey, students shared their attitudes and open-ended opinions toward the assignment and the videos. The findings suggest that having an assignment that incorporated videos was a useful addition to stimulate students' understanding of course materials. The videos were regarded positively along a number of important dimensions and motivated students to learn more about the advertising industry. This paper also includes five suggestions for incorporating the videos in an instructional setting.

Educational research findings suggest that instructors can foster the growth of thinking skills and promote science literacy by incorporating active learning strategies into the classroom. Active learning occurs when instructors build learner participation into classes. Learning in large, general education Earth Science classes was evaluated using formative assessment exercises conducted by students in groups. Bloom's taxonomy of cognitive development was used as a guide to identify critical thinking skills (comprehension, application, analysis, synthesis, evaluation) that could be linked to specific assessment methods such as conceptests, Venn diagrams, image analysis, concept maps, open-ended questions, and evaluation rubrics. Two instructors conducted a series of analyses on sample classes taught with traditional lecture and inquiry-based learning methods. Qualitative and quantitative analyses show that such methods are preferred by students, improve student retention, produce no decrease in content knowledge, promote deeper understanding of course material, and increase logical thinking skills.

A case study on using instructor-recorded videos in an upper level economics course

Because people are constantly confronted with numbers and mathematical concepts in the news, we have embarked on a project to create journalism that can support news users’ number skills. But doing so requires understanding (1) journalists’ ability to reason with numbers, (2) other adults’ ability to do so, and (3) the attributes and affordances of news. In this paper, we focus on the relationship between adults’ news habits and their quantitative reasoning skills. We collected data from a sample of 1,200 US adults, testing their ability to interpret statistical results and asking them to report their news habits. The assessment we developed differentiated the skills of adults in our sample and conformed to the theoretical and statistical assumption that such skills are normally distributed in the population overall. We also found that respondents could be clustered into six distinct groups on the basis of news repertoires (overall patterns of usage, including frequency of news use overall and choice of news outlets). As often assumed in the literature on quantitative reasoning, these news repertoires predicted quantitative reasoning skills better than the amount of quantification in the outlets, but they still predicted only a small fraction of the variance. These results may suggest that news habits may play a smaller or less direct role in quantitative reasoning than has previously been assumed. We speculate that the presence (or absence) of quantification in everyday activities – namely work and hobbies – may be a better predictor of adults’ quantitative reasoning, as may additional dimensions of news habits and affective responses to numbers.

Quantitative reasoning is considered a crucial prerequisite for acquiring domain-specific expertise in higher education. To ascertain whether students are developing quantitative reasoning, validly assessing its development over the course of their studies is required. However, when measuring quantitative reasoning in an academic study program, it is often confounded with other skills. Following a situated approach, we focus on quantitative reasoning in the domain of business and economics and define domain-specific quantitative reasoning primarily as a skill and capacity that allows for reasoned thinking regarding numbers, arithmetic operations, graph analyses, and patterns in real-world business and economics tasks, leading to problem solving. As many studies demonstrate, well-established instruments for assessing business and economics knowledge like the Test of Understanding College Economics (TUCE) and the Examen General para el Egreso de la Licenciatura (EGEL) contain items that require domain-specific quantitative reasoning skills. In this study, we follow a new approach and assume that assessing business and economics knowledge offers the opportunity to extract domain-specific quantitative reasoning as the skill for handling quantitative data in domain-specific tasks. We present an approach where quantitative reasoning – embedded in existing measurements from TUCE and EGEL tasks – will be empirically extracted. Hereby, we reveal that items tapping domain-specific quantitative reasoning constitute an empirically separable factor within a Confirmatory Factor Analysis and that this factor (domain-specific quantitative reasoning) can be validly and reliably measured using existing knowledge assessments. This novel methodological approach, which is based on obtaining information on students’ quantitative reasoning skills using existing domain-specific tests, offers a practical alternative to broad test batteries for assessing students’ learning outcomes in higher education.

Engaging non-science majors in a college-level science course can prove challenging. In turn, this can make it difficult to effectively teach science and math content. However, topics related to planetary exploration have a unique way of capturing one’s imagination and may serve to robustly engage non-science majors. In this contribution, I 1) describe a model rocketry lab module, I have created and implemented into an introductory-level planetary geology course and 2) quantify student learning gains as a result of this module. This module builds on model rocketry lesson plans for science and math coursework at the K-12 level (e.g., [1] [2]) and involves students working in groups to 1) design and build model rockets to carry out a theoretical mission that addresses a science question the students have developed, 2) launch their rockets and collect related data, 3) synthesize and evaluate their data, and 4) report their results in both oral and written forms. The tasks of building and launching the model rocket serve as a vehicle that allows students to employ the scientific process while learning about planetary mission design and applying geologic and quantitative skills useful to answering a science-related question. Quantification of student learning gains shows that through this lab module, students significantly improved their quantitative and scientific reasoning skills. Results from student questionnaires showed a significant increase in student interest and confidence in addressing scientific questions as well as an understanding of how planetary missions are designed and conducted.

Quantitative Reasoning (QR) is essential for today’s students, yet most higher education institutions have not effectively addressed this issue. This study investigates students’ quantitative reasoning in STEM and Non-STEM math pathways using a non-proprietary, NSF grant-funded instrument, the Quantitative Literacy & Reasoning Assessment (QLRA). Participants were students enrolled in at least one college-level math pathway course at a large public institution in the southeastern US. The results showed a significant difference between STEM and Non-STEM students’ QLRA scores, with STEM students (n = 244, M = 27%, SD = 16.21%) scoring, on average, about 6% higher than Non-STEM students (n = 295, M = 21.1%, SD =11.38%). STEM students who were further along in their math sequence, i.e. Pre-calculus/Trigonometry and Calculus I, had a higher QLRA score than those taking the gateway math courses in that pathway. Non-STEM students who took additional math courses also had a higher QLRA score than those in the entry-level math course. However, the students overall had relatively low QR skills (n = 539, M = 23.78%, SD = 14.07%). These results highlight the need for an increased understanding of the math pathways initiative and its relationship with quantitative reasoning. Thoughtful and deliberate scrutiny of curriculum and pedagogy is important in all math pathways as it relates to the development of quantitative reasoning skills.

Developing students’ understanding of cells and the microscopic scale is an important goal of biology education. Cells are the building blocks of multicellular organisms, and most of Earth’s biodiversity is found at the microscopic scale. Developing an understanding of the microscopic scale requires that students use their quantitative reasoning skills. Here, resources are presented that help students develop their quantitative reasoning skills and improve their understanding of the small scale of microscopic life. The crosscutting concept, Scale, Proportion, and Quantity, and the science and engineering practice, Using Mathematics and Computational Thinking, are highlighted. The development of students’ quantitative reasoning skills in biology is universally recognized as an important outcome of biology education.

Making an Online Summer Bridge Program High Touch Melissa Eblen-Zayas (bio) and Janet Russell (bio) Summer bridge programs are designed to ease the transition to college by providing students with academic skills and social resources during the summer between high school graduation and college. Research shows that bridge programs are potentially effective at increasing retention and academic success of at-risk students by providing an early orientation to the college experience and connecting these students with each other and the community (Thayer, 2000; Institute of Education Sciences, 2016); however, bridge programs can be expensive for institutions to operate, and the students who might benefit most from participation may not be able to commit to being on campus full-time during the summer. We developed a hybrid program to achieve many of the goals of a traditional summer bridge program, but with a flexible implementation that allowed students to remain at home to meet employment or family obligations. The 6-week summer portion of the program was entirely online, followed by on-campus, face-to-face weekly course meetings in the 10-week fall term. Students earned 6 credits for completion of the entire (summer and fall) program (typical courses at our institution carry 6 credits), and there was no cost to students to participate. For our residential, small liberal arts college, a bridge course that opened with a completely online portion was paradoxical—How do you create a high-touch, online program that captures key elements of what is a mostly residential and face-to-face experience for students? We had two main goals for the design and implementation of the 6-week summer online portion of the program: for participating students (a) to review and strengthen the quantitative skills seen in high school math classes, and (b) to connect with the college community before arriving on campus in the fall. As these goals suggest, this program blended elements of academic affairs and student affairs to create a rich learning experience built on research-based suggestions for supporting first-generation students (Pascarella, Pierson, Wolniak, & Terenzini, 2004), although the program was not limited to first-generation students. GROUNDING OUR PROGRAM IN THE LITERATURE The academic focus of this program was strengthening and reviewing quantitative skills. Research has shown that there are large disparities in the math preparation of students that can be traced back to early [End Page 104] educational periods that impact whether students are well-positioned for 2-year or 4-year college experiences (Lee, 2012), and for some demographic groups, college enhances quantitative literacy disparities (Baer, Cook, & Baldi, 2006). Even at selective liberal arts colleges similar to ours, there are significant retention and achievement gaps for students in quantitative fields (Brown, Coffey, Rachford, & Sambolín, 2017). Every student at our institution is required to complete three courses that include a quantitative reasoning exploration component; yet students’ high school preparation in quantitative topics up through precalculus varies immensely, and the college offers no remedial courses in math or quantitative reasoning. Because this program did not target students with particular academic interests (e.g., potential STEM majors), our goal was to review quantitative skills and also showcase the relevance of these skills to a variety of disciplines and career paths. First-generation college students are often unaware of the range of possible curricular and career options, but they benefit from explicit discussion of the possibilities (Parks-Yancy, 2012; Tate et al., 2015). Students were invited to participate based on ACT and SAT math scores that suggested they could benefit from quantitative skills review. Over 100 students were invited to apply, approximately 30–40 students followed through with an application, and we selected 20 students to participate, primarily based on a quantitative skills assessment and how students’ areas of needed improvement matched with the quantitative topics addressed by the program. The program topics were chosen based on conversations with faculty members in multiple disciplines, as well as assessments of students’ quantitative skills from previous years. We did not target particular demographic groups in our invitation or in our selection process, but the percentage of students eligible for U.S. Department of Education TRIO Student Services Support who participated in the...

Quantitative biology is a rapidly advancing field in the biological sciences, particularly given the rise of large datasets and computer processing capabilities that have continually expanded over the past 50years. Thus, the question arises, How should K-12 biology teachers incorporate quantitative biology skills into their biology curriculum? The teaching of quantitative biology has not been readily integrated into undergraduate biology curricula that impact preservice teachers. This has potential to cascade effects downward into the quality of learning about quantitative biology that can be expected in K-12 contexts. In this paper, we present the perspectives of a mathematics educator, a science educator, and two biologists, and discuss how we have personally incorporated aspects of quantitative reasoning into our courses. We identify some common challenges relevant to expanding implementation of quantitative reasoning in undergraduate biology courses in order to serve the needs of preservice teachers-both in their disciplinary courses and methods courses. For example, time constraints, math pedagogical content knowledge, and personal views about the relevance of quantitative principles in biology teaching and learning can impact how and to what extent they become implemented in curricula. In addition, although national standards at the K-12 level do address quantitative reasoning, the emphasis and guidance provided are sparser than for other content standards. We predict that both K-12 standards and guidelines for undergraduate education will only increase in their emphasis on quantitative skills as computation, "big data," and statistical modeling are increasingly becoming requisite skills for biologists.

In response to 21st-century demands for students’ Quantitative Reasoning Skills (QRS), the unique quantitative reasoning characteristics of the lower-secondary school chemistry, and the need for QRS assessment in the discipline, this study developed an instrument to assess Students’ Chemistry Quantitative Reasoning Skills (QRSC). The QRSC assessment, designed based on the SOLO taxonomy, curriculum standards, and the Higher Secondary School Entrance Examination (HSSEE) criteria, comprised 26 items and was administered to 237 students. After using Rasch analysis to score students’ performances, the study conducted descriptive statistics, independent samples t-tests, ANOVA, and the general linear model to analyse students’ overall QRSC, gender and academic achievements differences in QRSC, and the interactive effect between gender and academic achievement on QRSC. The results showed that the students’ overall QRSC level was relatively good and widely distributed. Gender had no significant effect on lower-secondary school students’ QRSC; however, there was a significant difference in QRSC among students with different academic achievements. In addition, the study found a significant interaction between gender and academic achievement in QRSC. Specifically, academic achievement can mediate the influence of gender on QRSC. Based on these findings, the study made some pedagogical recommendations for students’ QRSC development.

In the biosciences, quantitative skills are an essential graduate learning outcome. Efforts to evidence student attainment at the whole of degree programme level are rare and making sense of such data is complex. We draw on assessment theories from Sadler (evaluative expertise) and Boud (sustainable assessment) to interpret final-year bioscience students’ responses to an assessment task comprised of quantitative reasoning questions across 10 mathematical and statistical topics. The question guiding the study was: do final year science students graduate knowing the quantitative skills that they have, and knowing the quantitative skills that they do not have? Confidence indicators for the 10 topics gathered students’ perceptions of their quantitative skills. Students were assigned to one of four categories: high performance-high confidence; low performance-low confidence; high performance-low confidence; or low performance-high confidence – with those in the first two categories demonstrating evaluative expertise. Results showed the majority of students effectively evaluated their quantitative skills as low performance-low confidence. We argue that the application of evaluative expertise to make sense of this graduate learning outcome can further the debate on how assuring graduate learning outcomes can enhance student learning.

We have designed three laboratory modules for an introductory organismal biology course with an emphasis on quantitative reasoning and data analysis skills. Module 1 tests for dimorphism in crayfish chelae using a paired statistical design. Module 2 tests for allometric growth of tapeworm hook structures using a regression model. Module 3 tests for differences in stomatal densities between two groups of plants using a two-sample statistical approach. For all three modules, we emphasize the use of confidence intervals to draw statistical conclusions about hypotheses. Knowledge about the basic biology of animals and plants is required, including arthropods, platyhelminths, and vascular plants. Background reading on dimorphism, allometry, and transpiration provides the necessary foundation to develop questions and hypotheses. Some familiarity with R is necessary for both students and instructors, although the activities can be modified for analysis with Excel or another statistical package. These modules can be taught independently or together as a unit within a course. As stated in the AAAS document, <em>Vision and Change: A Call to Action</em>, the ability to use quantitative reasoning is a core competency that must be developed by all biology students. These modules address the call for instruction in quantitative reasoning and provide a hands-on active introduction to key tools that will be required to build students&rsquo; statistical repertoire in more advanced courses. <em>Primary Image:</em>&nbsp;A highlight of the three modules used in our introductory organismal biology course, including the use of calipers to test for dimorphism in the size of crayfish chelae (upper right), a leaf impression (lower right) from a hydrangea plant (lower left) used to test hypotheses about stomata densities, and the image of an <em>Echinococcus </em>tapeworm (upper left) to test hypotheses about allometry.&nbsp;&nbsp;