John E. Merrill

Photosynthetic inorganic carbon utilization and growth of Porphyra linearis (Rhodophyta)

Photosynthetic (oxygen evolution) and growth (biomass increase) responses to ambient pH and inorganic carbon (Ci) supply were determined for Porphyralinearis grown in 0.5 L glass cylinders in the laboratory, or in 40 L fibreglass outdoor tanks with running seawater. While net photosynthetic rates were uniform at pH 6.0–8.0, dropping only at pH 8.7, growth rates were significantly affected by pH levels other than that of seawater (c. pH 8.3). In glass cylinders, weekly growth rates averaged 76% at external pH 8.0, 13% at pH 8.7 and 26% at pH 7.0. Photosynthetic O2 evolution on a daily basis(i.e. total O2 evolved during day time less total O2 consumed during night time) was similar to the growth responses at all experimental pH levels, apparently due to high dark respiration rates measured at acidic pH. Weekly growth rates averaged 53% in algae grown in fibreglass tanks aerated with regular air (360 mg L-1 CO2) and 28% in algae grown in tanks aerated with CO2-enriched air (750 mg L-1 CO2). The pH of the seawater medium in which P. linear is was grown increased slightly during the day and only rarely reached 9.0. The pH at the boundary layer of algae submerged in seawater increased in response to light reaching, about pH 8.9 within minutes, or remained unchanged for algae submerged in a CO2-free artificial sea water medium. Photosynthesis of P. linearissaturated at Ci concentrations of seawater (K0.5560 μM at pH 8.2) and showed low photosynthetic affinity for CO2(K0.5 61 μM) at pH 6.0. It is therefore concluded that P. linearisuses primarily CO2 with HCO3- being an alternative source of Ci for photosynthesis. Its fast growth could be related to the enzyme carbonic anhydrase whose activity was detected intra- and extracellularly.

What Are They Thinking? Automated Analysis of Student Writing about Acid–Base Chemistry in Introductory Biology

Students’ writing can provide better insight into their thinking than can multiple-choice questions. However, resource constraints often prevent faculty from using writing assessments in large undergraduate science courses. We investigated the use of computer software to analyze student writing and to uncover student ideas about chemistry in an introductory biology course. Students were asked to predict acid–base behavior of biological functional groups and to explain their answers. Student explanations were rated by two independent raters. Responses were also analyzed using SPSS Text Analysis for Surveys and a custom library of science-related terms and lexical categories relevant to the assessment item. These analyses revealed conceptual connections made by students, student difficulties explaining these topics, and the heterogeneity of student ideas. We validated the lexical analysis by correlating student interviews with the lexical analysis. We used discriminant analysis to create classification functions that identified seven key lexical categories that predict expert scoring (interrater reliability with experts = 0.899). This study suggests that computerized lexical analysis may be useful for automatically categorizing large numbers of student open-ended responses. Lexical analysis provides instructors unique insights into student thinking and a whole-class perspective that are difficult to obtain from multiple-choice questions or reading individual responses.

Applying computerized-scoring models of written biological explanations across courses and colleges: prospects and limitations.

Our study explored the prospects and limitations of using machine-learning software to score introductory biology students’ written explanations of evolutionary change. We investigated three research questions: 1) Do scoring models built using student responses at one university function effectively at another university? 2) How many human-scored student responses are needed to build scoring models suitable for cross-institutional application? 3) What factors limit computer-scoring efficacy, and how can these factors be mitigated? To answer these questions, two biology experts scored a corpus of 2556 short-answer explanations (from biology majors and nonmajors) at two universities for the presence or absence of five key concepts of evolution. Human- and computer-generated scores were compared using kappa agreement statistics. We found that machine-learning software was capable in most cases of accurately evaluating the degree of scientific sophistication in undergraduate majors’ and nonmajors’ written explanations of evolutionary change. In cases in which the software did not perform at the benchmark of “near-perfect” agreement (kappa > 0.80), we located the causes of poor performance and identified a series of strategies for their mitigation. Machine-learning software holds promise as an assessment tool for use in undergraduate biology education, but like most assessment tools, it is also characterized by limitations.

Harnessing technology to improve formative assessment of student conceptions in STEM: Forging a national network

Concept inventories, consisting of multiple-choice questions designed around common student misconceptions, are designed to reveal student thinking. However, students often have complex, heterogeneous ideas about scientific concepts. Constructed-response assessments, in which students must create their own answer, may better reveal students’ thinking, but are time- and resource-intensive to evaluate. This report describes the initial meeting of a National Science Foundation–funded cross-institutional collaboration of interdisciplinary science, technology, engineering, and mathematics (STEM) education researchers interested in exploring the use of automated text analysis to evaluate constructed-response assessments. Participants at the meeting shared existing work on lexical analysis and concept inventories, participated in technology demonstrations and workshops, and discussed research goals. We are seeking interested collaborators to join our research community.

Development of nori markets in the western world

Extensive effort has been made over the past decade to introduce nori (species of Porphyra) farming in North America and other western countries. A key aspect has been the evaluation of markets within these countries and in the region as a whole. This report is an overview of relevant market data, including: (1) estimates of market sizes and values; (2) trends observed in these data over time, including extrapolations into the future; (3) typical market structures from producer to consumer; (4) examples of specific marketing efforts and their status. Possible activities that could enhance future prospects for these products within the markets of the western world are discussed.

Examining the Impact of Question Surface Features on Students’ Answers to Constructed-Response Questions on Photosynthesis

One challenge in science education assessment is that students often focus on question surface features rather than the underlying scientific principles. The authors investigated how student responses to photosynthesis constructed-response questions vary based on two surface features of a question and found no significant difference in the content of responses.

What Motivates Biology Instructors to Engage and Persist in Teaching Professional Development

This qualitative study uses expectancy-value theory to explore the motivation for college biology instructors to participate and persist in teaching professional development for 2.5 years.

A Faculty Professional Development Model That Improves Student Learning, Encourages Active-Learning Instructional Practices, and Works for Faculty at Multiple Institutions.

Helping faculty develop high-quality instruction that positively affects student learning can be complicated by time limitations, a lack of resources, and inexperience using student data to make iterative improvements. We describe a community of 16 faculty from five institutions who overcame these challenges and collaboratively designed, taught, iteratively revised, and published an instructional unit about the potential effect of mutations on DNA replication, transcription, and translation. The unit was taught to more than 2000 students in 18 courses, and student performance improved from preassessment to postassessment in every classroom. This increase occurred even though faculty varied in their instructional practices when they were teaching identical materials. We present information on how this faculty group was organized and facilitated, how members used student data to positively affect learning, and how they increased their use of active-learning instructional practices in the classroom as a result of participation. We also interviewed faculty to learn more about the most useful components of the process. We suggest that this professional development model can be used for geographically separated faculty who are interested in working together on a known conceptual difficulty to improve student learning and explore active-learning instructional practices.