High School Students' Proficiency and Confidence Levels in Displaying Their Understanding of Basic Electrolysis Concepts

This study was conducted with 330 Form 4 (grade 10) students (aged 15 – 16 years) who were involved in a course of instruction on electrolysis concepts. The main purposes of this study were (1) to assess high school chemistry students’ understanding of 19 major principles of electrolysis using a recently developed 2-tier multiple-choice diagnostic instrument, the Electrolysis Diagnostic Instrument (EDI), and (2) to assess students’ confidence levels in displaying their knowledge and understanding of these electrolysis concepts. Analysis of students’ responses to the EDI showed that they displayed very limited understanding of the electrolytic processes involving molten compounds and aqueous solutions of compounds, with a mean score of 6.82 (out of a possible maximum of 17). Students were found to possess content knowledge about several electrolysis processes but did not provide suitable explanations for the changes that had occurred, with less than 45 % of students displaying scientifically acceptable understandings about electrolysis. In addition, students displayed limited confidence about making the correct selections for the items; yet, in 16 of the 17 items, the percentage of students who were confident that they had selected the correct answer to an item was higher than the actual percentage of students who correctly answered the corresponding item. The findings suggest several implications for classroom instruction on the electrolysis topic that need to be addressed in order to facilitate better understanding by students of electrolysis concepts

An Evaluation of Methods for Inferring Boolean Networks from Time-Series Data

Regulatory networks play a central role in cellular behavior and decision making. Learning these regulatory networks is a major task in biology, and devising computational methods and mathematical models for this task is a major endeavor in bioinformatics. Boolean networks have been used extensively for modeling regulatory networks. In this model, the state of each gene can be either ‘on’ or ‘off’ and that next-state of a gene is updated, synchronously or asynchronously, according to a Boolean rule that is applied to the current-state of the entire system. Inferring a Boolean network from a set of experimental data entails two main steps: first, the experimental time-series data are discretized into Boolean trajectories, and then, a Boolean network is learned from these Boolean trajectories. In this paper, we consider three methods for data discretization, including a new one we propose, and three methods for learning Boolean networks, and study the performance of all possible nine combinations on four regulatory systems of varying dynamics complexities. We find that employing the right combination of methods for data discretization and network learning results in Boolean networks that capture the dynamics well and provide predictive power. Our findings are in contrast to a recent survey that placed Boolean networks on the low end of the ‘‘faithfulness to biological reality’’ and ‘‘ability to model dynamics’’ spectra. Further, contrary to the common argument in favor of Boolean networks, we find that a relatively large number of time points in the timeseries data is required to learn good Boolean networks for certain data sets. Last but not least, while methods have been proposed for inferring Boolean networks, as discussed above, missing still are publicly available implementations thereof. Here, we make our implementation of the methods available publicly in open source at http://bioinfo.cs.rice.edu/

An exploration of secondary students' mental states when learning about acids and bases

This study explored factors of students’ mental states, including emotion, intention, internal mental representation, and external mental representation, which can affect their learning performance. In evaluating students’ mental states during the science learning process and the relationship between mental states and learning achievement, valid, reliable, and scalable measures of students’ mental states and learning achievement are needed. This paper presents the development of the Mental State Conceptual Learning Inventory (MSCLI) to identify students’ mental states before and after learning about acids and bases. This instrument is time efficient and convenient and can be administered to large student samples so that teachers and researchers can gain profound insights into their students’ learning of acids and bases in science class. The results of this study indicate that students’ mental states are highly correlated with their achievement. As a whole, low-achieving students tended to have negative emotions and low intentions, were not good at internal visualization, and were unable to interpret graphics and draw pictures. In contrast, high-achieving students had positive emotions and intentions when learning life-related topics about acids and bases, and were good at internal visualization and drawing and interpreting graphics

Understanding interactions in face-to-face and remote undergraduate science laboratories

This paper reviews the ways in which interactions have been studied, and the findings of such studies, in science education in both face-to-face and remote laboratories. Guided by a systematic selection process, 27 directly relevant articles were analysed based on three categories: the instruments used for measuring interactions, the research findings on student interactions, and the theoretical frameworks used in the studies of student interactions. In face-to-face laboratories, instruments for measuring interactions and the characterisation of the nature of interactions were prominent. For remote laboratories, the analysis of direct interactions was found to be lacking. Instead, studies of remote laboratories were mainly concerned with their practical scope. In addition, it is found that only a limited number of theoretical frameworks have been developed and applied in the research design. Existent theories are summarised and possible theoretical frameworks that may be implemented in studies of interactions in undergraduate laboratories are proposed. Finally, future directions for research on the interrelationship between student interactions and laboratory learning are suggested

Challenging the Science Curriculum Paradigm: TeachingPrimary Children Atomic-Molecular Theory

Solutions to global issues demand the involvement of scientists, yet concern exists about retention rates in science as students pass through school into University. Young children are curious about science, yet are considered incapable of grappling with abstract and microscopic concepts such as atoms, sub-atomic particles, molecules and DNA. School curricula for primary (elementary) aged children reflect this by their limitation to examining only what phenomena are without providing any explanatory frameworks for how or why they occur. This research challenges the assumption that atomic-molecular theory is too difficult for young children, examining new ways of introducing atomic theory to 9 year olds and seeks to verify their efficacy in producing genuine learning in the participants. Early results in three cases in different schools indicate these novel methods fostered further interest in science, allowed diverse children to engage and learn aspects of atomic theory, and satisfied the children’s desire for intellectual challenge. Learning exceeded expectations as demonstrated in the post-interview findings. Learning was also remarkably robust, as demonstrated in two schools eight weeks after the intervention, and in one school, one year after their first exposure to ideas about atoms, elements and molecules

Design and Validation of an Instrument to Measure Students’ Interactions and Satisfaction in Undergraduate Chemistry Laboratory Classes

© 2020, Springer Nature B.V. This paper describes the development, final design and validation of an instrument that measures a range of student interactions and satisfaction in undergraduate chemistry laboratories. Student surveys or conceptual and attitudinal instruments are widely used techniques for collecting relevant information on student learning. However, there is a lack of specific instruments for collecting data on the relationships between social factors and learning. Consequently, this study attempted to fill this gap by introducing an instrument—the Interactions in Undergraduate Laboratory Classes (IULC). The design of the IULC instrument is based on the theory of distributed cognition, meaning that knowledge is not rooted in an individual’s mind, but develops in the process of interacting with the environment. The instrument covers three aspects: (i) frequency of interactions, (ii) satisfaction and (iii) importance of interactions for the specific laboratory. Undergraduate students (N = 204) enrolled in a first-year chemistry course participated in a test case for the instrument and the corresponding data were analysed using different methods for each of the three parts. The factor structure of the data obtained from the first part of the instrument and internal consistency measures are discussed. Among findings captured by the instrument, student-teacher (instructors in the university context) interactions correlated positively with students’ satisfaction levels. Implications and suggestions for the use of the instrument are discussed