Introductory programming: a systematic literature review

As computing becomes a mainstream discipline embedded in the school curriculum and acts as an enabler for an increasing range of academic disciplines in higher education, the literature on introductory programming is growing. Although there have been several reviews that focus on specific aspects of introductory programming, there has been no broad overview of the literature exploring recent trends across the breadth of introductory programming. This paper is the report of an ITiCSE working group that conducted a systematic review in order to gain an overview of the introductory programming literature. Partitioning the literature into papers addressing the student, teaching, the curriculum, and assessment, we explore trends, highlight advances in knowledge over the past 15 years, and indicate possible directions for future research

Modelling human teaching tactics and strategies for tutoring systems

One of the promises of ITSs and ILEs is that they will teach and assist learning in an intelligent manner. Historically this has tended to mean concentrating on the interface, on the representation of the domain and on the representation of the student’s knowledge. So systems have attempted to provide students with reifications both of what is to be learned and of the learning process, as well as optimally sequencing and adjusting activities, problems and feedback to best help them learn that domain. We now have embodied (and disembodied) teaching agents and computer-based peers, and the field demonstrates a much greater interest in metacognition and in collaborative activities and tools to support that collaboration. Nevertheless the issue of the teaching competence of ITSs and ILEs is still important, as well as the more specific question as to whether systems can and should mimic human teachers. Indeed increasing interest in embodied agents has thrown the spotlight back on how such agents should behave with respect to learners. In the mid 1980s Ohlsson and others offered critiques of ITSs and ILEs in terms of the limited range and adaptability of their teaching actions as compared to the wealth of tactics and strategies employed by human expert teachers. So are we in any better position in modelling teaching than we were in the 80s? Are these criticisms still as valid today as they were then? This paper reviews progress in understanding certain aspects of human expert teaching and in developing tutoring systems that implement those human teaching strategies and tactics. It concentrates particularly on how systems have dealt with student answers and how they have dealt with motivational issues, referring particularly to work carried out at Sussex: for example, on responding effectively to the student’s motivational state, on contingent and Vygotskian inspired teaching strategies and on the plausibility problem. This latter is concerned with whether tactics that are effectively applied by human teachers can be as effective when embodied in machine teachers

Neuro-fuzzy knowledge processing in intelligent learning environments for improved student diagnosis

In this paper, a neural network implementation for a fuzzy logic-based model of the diagnostic process is proposed as a means to achieve accurate student diagnosis and updates of the student model in Intelligent Learning Environments. The neuro-fuzzy synergy allows the diagnostic model to some extent "imitate" teachers in diagnosing students' characteristics, and equips the intelligent learning environment with reasoning capabilities that can be further used to drive pedagogical decisions depending on the student learning style. The neuro-fuzzy implementation helps to encode both structured and non-structured teachers' knowledge: when teachers' reasoning is available and well defined, it can be encoded in the form of fuzzy rules; when teachers' reasoning is not well defined but is available through practical examples illustrating their experience, then the networks can be trained to represent this experience. The proposed approach has been tested in diagnosing aspects of student's learning style in a discovery-learning environment that aims to help students to construct the concepts of vectors in physics and mathematics. The diagnosis outcomes of the model have been compared against the recommendations of a group of five experienced teachers, and the results produced by two alternative soft computing methods. The results of our pilot study show that the neuro-fuzzy model successfully manages the inherent uncertainty of the diagnostic process; especially for marginal cases, i.e. where it is very difficult, even for human tutors, to diagnose and accurately evaluate students by directly synthesizing subjective and, some times, conflicting judgments

Math Is More Than Numbers: Beginning Bilingual Teachers’ Mathematics Teaching Practices and Their Opportunities to Learn

In this article, the author provides results from a 3-year, longitudinal study that examined two novice bilingual teachers’ mathematics teaching practices and their professional opportunities to learn to teach. Primary data sources included videotaped mathematics lessons, teacher interviews, and field notes of their teacher preparation methods courses. Findings revealed that the teachers were oriented toward differing views of learning that shaped how they organized students’ learning of language and mathematics during classroom instruction. While both teachers used similar teaching strategies to support students’ development of mathematics specific literacies, there were variances in how the learners were positioned within the classroom community and how and which repertoires of language practices were available and used during mathematics instruction. The teachers’ differing orientations toward learning are traced to their own professional opportunities to learn to teach. The significance of recognizing both the acquisition and participation metaphors of learning and the development of linguistically and culturally relevant teacher education are discussed

A Case Study on Targeted Support Using TPACK Model for Newly Hired Secondary Mathematics Teachers

As teachers plan for instruction, technology integration is an important factor in the planning and implementation process. This is become imperative in a virtual learning environment for instructors to be competent (Gregory & Lodge, 2015). Problems exist with integrating technology that aligns with teaching and learning in content areas. Among the many possible factors that contribute to these problems is lack of understanding of technology, lack of support for teachers with technology, everchanging technology tools, inadequate training alignment to instruction, technology training that is not content-specific, lack of support with the integration of technology, pedagogy, and content (Koehler et al., 2013). This case study with an intervention focused on investigating the essential characteristics of planning and implementing lessons with newly hired secondary mathematics teachers. A mixed methods design was employed to provide triangulation of multiple data points to validate key findings. The TPACK (Technological, Pedagogical, and Content Knowledge) framework by Mishra and Koehler (2006) provided a guide for planning and implementing lessons as well as to build teachers\u27 confidence in the integration of technology during instruction. Through planning interviews, survey data, class observations, teacher reflections, field notes, and teacher artifacts of lessons, the researcher examined the essential characteristics of planning and implementing a lesson using the TPACK model. Findings indicated that use of the TPACK model provided support for newly hired mathematics teachers in their incorporation of technology into instruction. Eight implications emerged from the findings in the study: using the TPACK survey to customize training for teachers by identifying areas of support, using the TPACK model for virtual planning, contextual knowledge in virtual classrooms, comprehending technology, implications of software-focused and use of sample lessons, virtual professional development with TPACK model, level of support with TPACK Planning, and TPACK survey interviews. This research informs practitioners and researchers to understand the complexity of teaching and the importance of providing differentiated support and training based on the needs of new teachers

Building capacity for professional development: the development of teachers as facilitators in Ghana

In low and middle income countries, cascade models of teacher professional development are often used as routes to educational reform. In these models, external agents deliver professional development which is then disseminated by in-country facilitators. However, little is known about how to support facilitators of professional development, particularly in low and middle income countries. In this study, we report on a model of capacity building for professional development in Ghana. In the context of a large-scale programme of science teacher professional development, a group of Ghanaian teachers gradually assumed responsibility for professional development facilitation, working alongside experienced facilitators from the UK. Using interviews focussed on a storyline technique, we explore the experiences of the Ghanaian teachers as they reflected on their roles. We found the teachers’ epistemological beliefs about teaching were coherent with those of the programme and suggest that this may be an important factor in the success of cascade models of professional development. The teachers gained self-confidence and improved their knowledge and skills of teaching and of professional development facilitation. We propose that this is useful learning for all facilitators and that the model described here is one which is potentially useful for capacity building in other contexts

Impact Philanthropy to Improve Teaching Quality: Focus on High-Need Secondary Students

Offers models for improving teachers' skills, including through apprenticeships and in-school mentoring; for creating an environment for great teaching through better leadership and whole-school reform; and guidance for donors on the policy environment

Sentiment Analysis in the Era of Web 2.0: Applications, Implementation Tools and Approaches for the Novice Researcher

Nowadays, people find it easier to express opinions via social media-formally known as Web 2.0. Sentiment analysis is an essential field under natural language processing in Computer Science that deals with analyzing people's opinions on the subject matter and discovering the polarity they contain. These opinions could be processed in collective form (as a document) or segments or units as sentences or phrases. Sentiment analysis can be applied in education, research optimization, politics, business, education, health, science and so on, thus forming massive data that requires efficient tools and techniques for analysis. Furthermore, the standard tools currently used for data collection, such as online surveys, interviews, and student evaluation of teachers, limit respondents in expressing opinions to the researcher's surveys and could not generate huge data as Web 2.0 becomes bigger. Sentiment analysis techniques are classified into three (3): Machine learning algorithms, lexicon and hybrid. This study explores sentiment analysis of Web 2.0 for novice researchers to promote collaboration and suggest the best tools for sentiment data analysis and result efficiency. Studies show that machine learning approaches result in large data sets on document-level sentiment classification. In some studies, hybrid techniques that combine machine learning and lexicon-based performance are better than lexicon. Python and R programming are commonly used tools for sentiment analysis implementation, but SentimentAnalyzer and SentiWordnet are recommended for the novice. Keywords:   Sentiment Analysis; Web 2.0; Applications; Tools; Novic

AN INVESTIGATION OF HIGH SCHOOL STUDENTS’ AND TEACHERS’ PERCEPTIONS OF ACADEMIC ACHIEVEMENT AND UNDERACHIEVEMENT

This study investigated high school students’ and teachers’ perceptions of academic self-perception, environmental perceptions, goal valuation, and motivation/self-regulation as factors affecting students’ academic achievement. A two-way MANOVA was conducted to determine if high school students’ gender and academic programs, Non-Honors/Non-Advanced Placement (AP) and Honors/Advanced Placement (AP), differed in their perceptions of academic self-perception, attitudes towards teachers and classes, attitudes towards school, goal valuation, and motivation/self-regulation using the School Attitude Assessment Survey-Revised. Students in the Honors/AP program had higher levels of academic self-perception and motivation/self-regulation than Non-Honors/Non-AP students’ results. Females had higher levels of motivation/self-regulation than males while males possessed greater attitudes towards school results. A stepwise multilinear regression was conducted to determine if gender, academic self-perception, attitudes towards teachers and classes, attitudes towards school, and motivation/self-regulation were predictors of students’ academic achievement as indicated by their self-reported grade point average (GPA). High school students’ academic self-perception and motivation/self-regulation were significant predictors of their academic achievement results. A one-way MANOVA was conducted using data from the Student Achievement Inventory: Teacher Form to determine if high school teachers’ perceptions of their students’ levels of academic self-efficacy, goal valuation, environmental perceptions, and motivation/self-regulation as factors affecting their academic achievement varied according to teacher experience. No statistical differences existed between the teachers’ level experience, as determined by their years spent teaching, and their perceptions of their students’ levels of academic self-efficacy, goal valuation, environmental perceptions, and motivation/self-regulation as factors affecting academic achievement. This study also sought to identify the students’ and teachers’ perceptions of factors impacting high school students’ underachievement and to determine possible solutions to support students’ their achievement. A general qualitative study consisting of high school teachers and their students was conducted using High School Students’ Views on Doing Well in School and High School Teachers’ Views on Doing Well in School surveys to determine causes of and solutions to underachievement. An interpretational analysis of the data revealed the emergence of environmental factors affecting student achievement, motivation, student attendance, students’ behaviors and skills, and support services and strategies as core categories affecting high school students’ academic achievement

A Qualitative Case Study of the Influence of Action Research on the Teaching Practices of Novice Secondary Mathematics Teachers

This qualitative case study was a means to examine the experiences of novice mathematics teachers as they progressed through the implementation cycle of action research in their graduate coursework and the subsequent effects of the experiences on their teaching practices during their clinical experience. An action research course for novice mathematics teachers can help them develop the pedagogical skills they need to succeed in their classrooms (Ulvik, 2014). Despite a wealth of literature on action research, there has been little study of how the experiences in an action research course can influence the teaching practices of novice secondary mathematics teachers during their coursework and clinical experience. Kolb’s experiential learning theory and the National Council of Teachers of Mathematics’ eight effective teaching practices served as the conceptual underpinnings for this study. The research questions were: (a) How do the experiences in an action research course influence the teaching practices of mathematics teachers? and (b) How do the action research experiences align with Kolb’s experiential learning theory? Four novice secondary mathematics teachers in a master’s degree program participated in this study. Data collection included interviews, observations, lesson plans, participants’ journals, synchronous discussions, action research proposals, digital dossiers, a survey, and the action research syllabus. Qualitative data analysis of the journals, synchronous discussions, literature reviews, and action plans resulted in three themes: (a) engagement in action research cultivated novice mathematics teachers’ sense of community and collaboration for sharing effective strategies that became evident in their classroom instruction, (b) exploring and unpacking scholarly literature through action research strengthened the pedagogical content knowledge of novice mathematics teachers and promoted their use of evidence-based practices, and (c) reflective journaling in action research resulted in novice mathematics teachers having the capacity to assess the effects of their teaching on student learning. These themes describe the influence of the action research experiences on the teaching practices of novice mathematics teachers. The findings show that an action research course embedded in a teacher preparation program during the coursework and clinical experience can positively impact the teaching practices of novice mathematics teachers