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Reviewing bodies have shown that a high percentage of SHS students tend to underperform in mathematics examinations. In that respect, we examined the influence of two teaching approaches on Ghanaian public Senior High School students' mathematical mindsets. A quantitative research design was used, that is, an ex post facto research design was used for this study. A total sample of 366 respondents was involved in this study. Two sets of questionnaires were employed for the study which are the students' perceptions of teaching approaches and mathematical mindset questionnaires. Descriptive analysis such as means and frequencies were used to analyze the data. The results revealed a possible influence of the teaching approaches students experienced and their mathematical mindset. That is, students taught with a student-centered approach were found to generally possess a growth mindset while those identified as possessing a more fixed mindset were mostly students taught using a more teacher-centered approach. The study recommended that teachers should adopt a student-centered approach to teaching since it has the potential to shape students' mindset toward a strong growth mindset, as students who have a growth mindset are more likely to succeed in school and beyond.

The study examined the factors that influence the performance of students in selected public junior high schools in Ghana using English Language, Mathematics and Science as cases and also to determine whether these observed performances support the continued implementation of the national policy on progression. In all, 98 teachers and 982 Junior High School (JHS) 2 students were randomly selected from three districts in the Central Region of Ghana. Data were analyzed using descriptive statistics (percentages and means) and standard deviation. It was found that the majority of the research participants' levels of attainment in English Language, Mathematics and Science did not permit automatic progression. Also, it was found that several teacher factors such as the inability to complete the planned curriculum due to numerous co-curricular activities and their challenges in teaching some of the topics may have contributed to the low performance of the students. Recommendations for the need to collect data on students' performance regularly at the various grade levels through assessment/tests to identify students' learning difficulties early and offer appropriate interventions to support such learners have been made to further strengthen the progression policy.

This paper draws on self-determination theory (SDT) to explore reasons for college students' decisions to either continue or change directions (and hence their persistence) from their STEM-intending majors. We therefore sought to gain insight into why some college students persisted in their STEM-intending degree programs while others, faced with the same challenge(s), changed majors. Using a phenomenological design, three students were purposefully selected and interviewed using a semi-structured interview guide. A finding from this study is that while challenges are a part of life, individual responses to academic challenges vary depending on how they judge the situation. For the three focal students, decisions about whether to persist in their STEM-intending degree programs involved a complex mix of factors. These were whether they found the challenge worthwhile (i.e., perception of autonomy), had a desire to engage in the STEM program because they found the program worthwhile (i.e., perception of competency) or had adequate support systems available (i.e., perception of relatedness). Implications for university authorities and college professors are highlighted.

The study examined the factors that influence the performance of students in selected public junior high schools in Ghana using English Language, Mathematics and Science as cases and also to determine whether these observed performances support the continued implementation of the national policy on progression. In all, 98 teachers and 982 Junior High School (JHS) 2 students were randomly selected from three districts in the Central Region of Ghana. Data were analyzed using descriptive statistics (percentages and means) and standard deviation. It was found that the majority of the research participants’ levels of attainment in English Language, Mathematics and Science did not permit automatic progression. Also, it was found that several teacher factors such as the inability to complete the planned curriculum due to numerous co-curricular activities and their challenges in teaching some of the topics may have contributed to the low performance of the students. Recommendations for the need to collect data on students’ performance regularly at the various grade levels through assessment/tests to identify students’ learning difficulties early and offer appropriate interventions to support such learners have been made to further strengthen the progression policy.

An active object recognition system has the advantage of acting in the environment to capture images that are more suited for training and lead to better performance at test time. In this paper, we utilize deep convolutional neural networks for active object recognition by simultaneously predicting the object label and the next action to be performed on the object with the aim of improving recognition performance. We treat active object recognition as a reinforcement learning problem and derive the cost function to train the network for joint prediction of the object label and the action. A generative model of object similarities based on the Dirichlet distribution is proposed and embedded in the network for encoding the state of the system. The training is carried out by simultaneously minimizing the label and action prediction errors using gradient descent. We empirically show that the proposed network is able to predict both the object label and the actions on GERMS, a dataset for active object recognition. We compare the test label prediction accuracy of the proposed model with Dirichlet and Naive Bayes state encoding. The results of experiments suggest that the proposed model equipped with Dirichlet state encoding is superior in performance, and selects images that lead to better training and higher accuracy of label prediction at test time.

Previous studies have reported the influence of professional development (PD) on participating teachers' identities. However, "what" goes on in PDs, "how" and "why" they shape particular identities require further investigation. This study contributes in this direction by drawing on the notions of "practice-linked identities" and "identity resources" to examine how two teachers' mathematics teaching identities developed following their interactions with the resources offered in a particular PD. We argue that their developing mathematics teaching identities appeared to be linked to their backgrounds and initial motivations for joining the PD, which in turn influenced their selective interaction with resources. Implications for research and PD are discussed.

Infants are biologically prepared to learn complex behaviors by interacting in dynamic, responsive social environments. Although the importance of interactive social experiences has long been recognized, current methods for studying complex multimodal interactions are lagging. This paper outlines a systems approach for characterizing fine-grained temporal dynamics of developing social interaction. We provide best practices for capturing, coding, and analyzing interaction activity on multiple-temporal scales, from fractions of seconds (e.g., gaze shifts), to minutes (e.g., coordinated play episodes), to weeks or months (e.g., developmental change). © 2013 IEEE.

This project characterizes the development of early social interactions in a longitudinal sample of mothers and their infants. To do this we track the interaction in as a temporal configuration of multimodal, multiparty components, coding a total of 14 dimensions at each frame. Our final goal is to develop methods which we can use to systematically document regularities in the way attention gets organized longitudinally in a large sample of mother-infant dyads. Coding systematically at this scale allows us to ground a developmental account of early social interaction. For this project, we developed 1) ways to reduce the labor intensity of coding frame-by-frame multidimensional data over the entire sample and 2)ways of quantifying complex configural regularities across our sample. © ACM 2010.

Reviewing bodies have shown that a high percentage of SHS students tend to underperform in mathematics examinations. In that respect, we examined the influence of two teaching approaches on Ghanaian public Senior High School students' mathematical mindsets. A quantitative research design was used, that is, an ex post facto research design was used for this study. A total sample of 366 respondents was involved in this study. Two sets of questionnaires were employed for the study which are the students' perceptions of teaching approaches and mathematical mindset questionnaires. Descriptive analysis such as means and frequencies were used to analyze the data. The results revealed a possible influence of the teaching approaches students experienced and their mathematical mindset. That is, students taught with a student-centered approach were found to generally possess a growth mindset while those identified as possessing a more fixed mindset were mostly students taught using a more teacher-centered approach. The study recommended that teachers should adopt a student-centered approach to teaching since it has the potential to shape students' mindset toward a strong growth mindset, as students who have a growth mindset are more likely to succeed in school and beyond. [ABSTRACT FROM AUTHOR]