Matching Items (4)

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Evaluation of Collaborative Learning in a Blended Biology Course at ASU

Description

Collaborative learning has been found to enhance student learning experiences through interaction with peers and instructors in a way that typically does not occur in a traditional lecture course. However,

Collaborative learning has been found to enhance student learning experiences through interaction with peers and instructors in a way that typically does not occur in a traditional lecture course. However, more than half of all collaborative learning structures have failed to last very long after their initial introductions which makes understanding the factors of collaboration that make it successful very important. The purpose of this study was to evaluate collaborative learning in a blended learning course to gauge student perceptions and the factors of collaboration and student demographics that impact that perception. This was done by surveying a sample of students in BIO 282 about their experiences in the BIO 281 course they took previously which was a new introductory Biology course with a blended learning structure. It was found that students agree that collaboration is beneficial as it provides an opportunity to gain additional insight from peers and improve students' understanding of course content. Also, differences in student gender and first generation status have less of an effect on student perceptions of collaboration than differences in academic achievement (grade) bracket.

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Created

Date Created
  • 2014-05

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Effects of Self-Guided Displays and Associated Interactive Elements on Visitor Knowledge, Attitudes, and Values

Description

Free-choice learning environments provide visitors with unique opportunities to observe and learn voluntarily and can serve as valuable educational opportunities. Incorporating interactive elements into displays have been shown to increase

Free-choice learning environments provide visitors with unique opportunities to observe and learn voluntarily and can serve as valuable educational opportunities. Incorporating interactive elements into displays have been shown to increase visitor dwell time and, ultimately, enhance the displays’ impacts on visitor knowledge and positive attitudes. This is especially important in free-choice learning environments where the visitor controls what display to visit and for how long. Visitors may not benefit from the display if they are not engaged with some attention-holding component. Interactive elements can greatly benefit a display’s potential to strengthen a visitor’s conservation attitudes and values of non-charismatic species that are traditionally less engaging due to their lack of activity or their appearance. This study examined the effect of a self-guided display with or without the incorporation of interactive elements on a visitors knowledge, attitude, and value of rattlesnakes. In Spring 2019, university biology students took surveys before (pre-survey) and after (post-survey) visiting a live animal rattlesnake display on campus. This was repeated in the Fall 2019 except that eight interactive elements were incorporated into the rattlesnakes displays. The pre and post-surveys were designed to evaluate the effect of the displays on student knowledge, attitudes, and values towards rattlesnakes. Paired t-tests revealed that visiting the displays increased student knowledge, attitude, and value of rattlesnakes, but that this effect was not enhanced by adding the interactive elements to the display. The results also showed that visiting the displays increased visitor dwell time, positively influenced one’s interest in revisiting the displays, and, overall provided visitors with enjoyment. These results provide further evidence that self-guided, live animal displays are impactful on increasing visitor knowledge, attitude, and value. However, the results also demonstrate that interactive elements do not necessarily enhance a display’s value, so further research should be conducted to determine key traits of effective interactive elements. This data and that from future related studies can have powerful conservation implications by informing on how displays can be optimized to achieve desired objectives.

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Created

Date Created
  • 2020

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Biology question generation from a semantic network

Description

Science instructors need questions for use in exams, homework assignments, class discussions, reviews, and other instructional activities. Textbooks never have enough questions, so instructors must find them from other

Science instructors need questions for use in exams, homework assignments, class discussions, reviews, and other instructional activities. Textbooks never have enough questions, so instructors must find them from other sources or generate their own questions. In order to supply instructors with biology questions, a semantic network approach was developed for generating open response biology questions. The generated questions were compared to professional authorized questions.

To boost students’ learning experience, adaptive selection was built on the generated questions. Bayesian Knowledge Tracing was used as embedded assessment of the student’s current competence so that a suitable question could be selected based on the student’s previous performance. A between-subjects experiment with 42 participants was performed, where half of the participants studied with adaptive selected questions and the rest studied with mal-adaptive order of questions. Both groups significantly improved their test scores, and the participants in adaptive group registered larger learning gains than participants in the control group.

To explore the possibility of generating rich instructional feedback for machine-generated questions, a question-paragraph mapping task was identified. Given a set of questions and a list of paragraphs for a textbook, the goal of the task was to map the related paragraphs to each question. An algorithm was developed whose performance was comparable to human annotators.

A multiple-choice question with high quality distractors (incorrect answers) can be pedagogically valuable as well as being much easier to grade than open-response questions. Thus, an algorithm was developed to generate good distractors for multiple-choice questions. The machine-generated multiple-choice questions were compared to human-generated questions in terms of three measures: question difficulty, question discrimination and distractor usefulness. By recruiting 200 participants from Amazon Mechanical Turk, it turned out that the two types of questions performed very closely on all the three measures.

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Agent

Created

Date Created
  • 2015

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Examination of the state-dependency and consequences of foraging in a low-energy system, the Gila monster, Heloderma suspectum

Description

Foraging has complex effects on whole-organism homeostasis, and there is considerable evidence that foraging behavior is influenced by both environmental factors (e.g., food availability, predation risk) and the physiological condition

Foraging has complex effects on whole-organism homeostasis, and there is considerable evidence that foraging behavior is influenced by both environmental factors (e.g., food availability, predation risk) and the physiological condition of an organism. The optimization of foraging behavior to balance costs and benefits is termed state-dependent foraging (SDF) while behavior that seeks to protect assets of fitness is termed the asset protection principle (APP). A majority of studies examining SDF have focused on the role that energy balance has on the foraging of organisms with high metabolism and high energy demands ("high-energy systems" such as endotherms). In contrast, limited work has examined whether species with low energy use ("low-energy systems" such as vertebrate ectotherms) use an SDF strategy. Additionally, there is a paucity of evidence demonstrating how physiological and environmental factors other than energy balance influence foraging behavior (e.g. hydration state and free-standing water availability). Given these gaps in our understanding of SDF behavior and the APP, I examined the state-dependency and consequences of foraging in a low-energy system occupying a resource-limited environment - the Gila monster (Heloderma suspectum, Cope 1869). In contrast to what has been observed in a wide variety of taxa, I found that Gila monsters do not use a SDF strategy to manage their energy reserves and that Gila monsters do not defend their energetic assets. However, hydration state and free-standing water availability do affect foraging behavior of Gila monsters. Additionally, as Gila monsters become increasingly dehydrated, they reduce activity to defend hydration state. The SDF behavior of Gila monsters appears to be largely driven by the fact that Gila monsters must separately satisfy energy and water demands with food and free-standing water, respectively, in conjunction with the timescale within which Gila monsters balance their energy and water budgets (supra-annually versus annually, respectively). Given these findings, the impact of anticipated changes in temperature and rainfall patterns in the Sonoran Desert are most likely going to pose their greatest risks to Gila monsters through the direct and indirect effects on water balance.

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Agent

Created

Date Created
  • 2014