Comparing first- and third-person perspectives in early elementary learning of honeybee systems

Prior literature has begun to demonstrate that even young children can learn about complex systems using participatory simulations. This study disentangles the impacts of third-person perspectives (offered by traditional simulations) and first-person perspectives (offered by participatory simulations) on children’s development of such systems thinking in the context of the emergent complexity of honeybee nectar foraging. Specifically, we worked with three first-grade classrooms assigned to one of three conditions—instruction through use of a first-person perspective only, third-person perspective only, and integrated instruction—to engage ideas of complex systems thinking. In each condition, systems concepts were targeted through instruction and assessment. The integrated and third-person classrooms demonstrated significant gains while the first-person classroom showed gains that were not statistically significant, suggesting that third-person perspectives play a critical role in how children learn systems thinking. This work also puts forth a novel assessment design for young children using multiple-choice questions.

     

Chaos: exploring an engaging online model for rapid application during the pandemic

Educational technology research and development - This paper is in response to the article entitled “A design framework for enhancing engagement in student-centered learning: own it, learn...     

Preschoolers’ Visual Attention during Electronic Storybook Reading as Related to Different Types of Textual Supports

Preschoolers’ (n?=?32) attention to print and pictures was documented during an electronic storybook reading session. Children (M?=?51.06 months; SD?=?7.34 months) looked at a 12-page book that contained three types of pages, each of which was presented four times over the course of the book: (1) silent presentation of print, (2) print that was read aloud, and (3) print that was both read aloud and highlighted. Our research objectives were to analyze whether the way in which print was presented related to the ways in which children attended to print and pictures during the reading session. Gaze fixation duration to print and pictures was assessed using a Tobii X2-60 portable eye tracking unit, which captured corneal reflection data for each child. Children’s total fixation duration to print was greatest when print was read aloud and highlighted as compared to when it was presented silently or read aloud. In addition, children looked at print more when it was displayed silently than when the computer read the story to children, although this difference was much smaller in magnitude. Children attended to pictures more than print across pages, but this difference was most notable when the story was read aloud. Results demonstrate the potential utility of nonverbal print referencing strategies during book reading.     

A person‐in‐context approach to student engagement in science: Examining learning activities and choice

Science education reform efforts in the Unites States call for a dramatic shift in the way students are expected to engage with scientific concepts, core ideas, and practices in the classroom. This new vision of science learning demands a more complex conceptual understanding of student engagement and research models that capture both the multidimensionality and contextual specificity of student engagement in science. In a unique application of person‐oriented analysis of experience sampling data, we employ cluster analysis to identify six distinct momentary engagement profiles representing different combinations of the behavioral, cognitive, and affective dimensions of student engagement in high school science classrooms. Students spend a majority of their classroom time in one of several engagement profiles characterized by high engagement on one dimension, but low levels on the others. Students exhibited low engagement across all three dimensions of engagement in about 22% of our observations. Full engagement, or high levels across all three dimensions, is the least frequent profile, occurring in only 11% of the observations. Students’ momentary engagement profiles are related in meaningful ways to both the learning activity in which students are engaged and the types of choices they are afforded. Laboratory activities provided especially polarized engagement experiences, producing full engagement, universally low engagement, and pleasurable engagement in which students are affectively engaged but are not engaged cognitively or behaviorally. Student choice is generally associated with more optimal engagement profiles and the specific type of choice matters in important ways. Choices about how to frame the learning activity have the most positive effects relative to other types of choices, such as choosing whom to work with or how much time to take. Results are discussed in terms of implications for practice and the utility of the methodological approach for evaluating the complexities of student engagement in science classrooms. © 2017 Wiley Periodicals, Inc. J Res Sci Teach 88: 19–43, 2018     

Transgender and Gender-Nonconforming Student Experiences in Christian Higher Education: A Qualitative Exploration

Religion and spirituality are important in the lives of many transgender and gender-nonconforming (TGNC) individuals. Although TGNC students can make unique contributions to Christian colleges and universities (CCUs), many individuals who identify as both religious and TGNC report rejection from nonaffirming religious communities that view TGNC identities and expression as sinful or psychologically disordered. Additionally, previous research has suggested that TGNC college students experience disproportionately high rates of verbal and sexual harassment, threats, physical assault, and anti-TGNC messaging on college campuses. In order to better understand the experiences of TGNC students who attended nonaffirming CCUs, semistructured interviews were conducted with seven TGNC students and alumni regarding their gender identity, religion, spirituality, campus experiences, and perceptions of campus climate. Data analysis was completed using guidelines consistent with Interpretative Phenomenological Analysis (Shaw, 2010). Findings revealed four major themes: (a) invisibility of TGNC individuals and identities on campus, (b) rejection within the college environment, (c) ambivalence and psychological conflict about integrating religion, spirituality, and gender identity, and (d) resilience and the importance of campus support systems. Recommendations for creating greater inclusion of TGNC students on CCU campuses are presented. This study also explores clinical considerations for mental health professionals and student services personnel employed at CCUs.     

Many districts left behind: An individual change analysis of inequity in the Kenyan primary educational opportunities (2001–2007)

The study examined variations in district performance in KCPE national examination in Kenya between 2001 and 2007. The individual change model revealed that district poverty rate was not a significant predictor of either the initial district performance (2001) or the rate of change over the seven-year period. The regional context of North Eastern Province had the lowest initial KCPE performance rates followed by the Gusii districts of Nyanza. However, the model revealed that the KCPE performance rates among districts located in the North Eastern Province are predicted to improve at an annual rate of 10.31 percentage points. The study recommends that educators and policy makers seek ways to address educational under-performance and low participation rates in Kenya without over-reliance on poverty reduction programs alone.     

Asymmetric Missing-data Problems: Overcoming the Lack of Negative Data in Preference Ranking

In certain classification problems there is a strong a asymmetry between the number of labeled examples available for each of the classes involved. In an extreme case, there may be a complete lack of labeled data for one of the classes while, at the same time, there are adequate labeled examples for the others, accompanied by a large body of unlabeled data. Since most classification algorithms require some information about all classes involved, label estimation for the un-represented class is desired. An important representative of this group of problems is that of user interest/preference modeling where there may be a large number of examples of what the user likes with essentially no counterexamples.Recently, there has been much interest in applying the EM algorithm to incomplete data problems in the area of text retrieval and categorization. We adapt this approach to the asymmetric case of modeling user interests in news articles, where only labeled positive training data are available, with access to a large corpus of unlabeled documents. User modeling is here equivalent to that of user-specific document ranking. EM is used in conjunction with the Naive Bayes model while its output is also utilized by a Support Vector Machine and Rocchio's technique.Our findings demonstrate that the EM algorithm can be quite effective in modeling the negative class under a number of different initialization schemes. Although primarily just the negative training examples are needed, a natural question is whether using all of the estimated labels (i.e., positive and negative) would be more (or less) beneficial. This is important considering that, in this context, the initialization of the negative class for EM is likely not to be very accurate. Experimental results suggest that EM output should be limited to negative label estimates only.