Investigating Student Learning and Perceptions Through Concept Journaling: An Exploratory Case Study in Coordinate Algebra

In order for students to comprehend mathematics, they must be able to think and apply learned knowledge to inform skill acquisition (Schoenfeld, 2013). Written communication is a skill that enables students to prepare to learn mathematics and express thoughts. Using qualitative case study methodology within symbolic interactionism framework, this study examined the effect of concept journaling on the learning of seven students in one high school Coordinate Algebra classroom. The study further explored how these students perceived concept journaling as a tool for learning mathematics. Concept journaling is defined as a type of writing activity using prompts that incorporate graphs, charts, real-world situations, mathematical formulas, diagrams, images, symbolic text, or other appropriate resources for the student to reflect, communicate, and express mathematical ideas through writing. The students were interviewed at the beginning and end of the research. After a lesson was taught a concept journaling activity was assigned and the students were observed while engaged in a writing activity. Data was triangulated and collected using four techniques: interviews, observations, concept journals, and researcher/teacher’s journal. Data analysis focused on comparing and contrasting themes that emerged through the detailed examination of the data. The following are emerging themes regarding student learning: through concept journaling (1) students learned by building associations of ideas utilizing their prior knowledge and experiences, (2) created a space for negotiating meaningful connections using multiple resources, and (3) provided opportunities for constructing meaning in context via peer communications and exchanges of personal views and ideas. The following are emerging themes regarding student perceptions: concept journaling was (4) seen as a meaningful experience to further their understanding of mathematics using real-world applications, (5) viewed by students as a medium to develop an awareness of the self while immersed in meaning making contexts, and (6) students expressed a sense of connection to mathematics through the use of concept journaling writing activities. Moreover, the findings highlighted a need for more focus on journaling in mathematics, longitudinal studies on writing in mathematics, and the students’ voices appearing in future literature

Language acquisition and machine learning

In this paper, we review recent progress in the field of machine learning and examine its implications for computational models of language acquisition. As a framework for understanding this research, we propose four component tasks involved in learning from experience - aggregation, clustering, characterization, and storage. We then consider four common problems studied by machine learning researchers - learning from examples, heuristics learning, conceptual clustering, and learning macro-operators - describing each in terms of our framework. After this, we turn to the problem of grammar acquisition, relating this problem to other learning tasks and reviewing four AI systems that have addressed the problem. Finally, we note some limitations of the earlier work and propose an alternative approach to modeling the mechanisms underlying language acquisition

Machine learning : techniques and foundations

The field of machine learning studies computational methods for acquiring new knowledge, new skills, and new ways to organize existing knowledge. In this paper we present some of the basic techniques and principles that underlie AI research on learning, including methods for learning from examples, learning in problem solving, learning by analogy, grammar acquisition, and machine discovery. In each case, we illustrate the techniques with paradigmatic examples

Machine learning and its applications in reliability analysis systems

In this thesis, we are interested in exploring some aspects of Machine Learning (ML) and its application in the Reliability Analysis systems (RAs). We begin by investigating some ML paradigms and their- techniques, go on to discuss the possible applications of ML in improving RAs performance, and lastly give guidelines of the architecture of learning RAs. Our survey of ML covers both levels of Neural Network learning and Symbolic learning. In symbolic process learning, five types of learning and their applications are discussed: rote learning, learning from instruction, learning from analogy, learning from examples, and learning from observation and discovery. The Reliability Analysis systems (RAs) presented in this thesis are mainly designed for maintaining plant safety supported by two functions: risk analysis function, i.e., failure mode effect analysis (FMEA) ; and diagnosis function, i.e., real-time fault location (RTFL). Three approaches have been discussed in creating the RAs. According to the result of our survey, we suggest currently the best design of RAs is to embed model-based RAs, i.e., MORA (as software) in a neural network based computer system (as hardware). However, there are still some improvement which can be made through the applications of Machine Learning. By implanting the 'learning element', the MORA will become learning MORA (La MORA) system, a learning Reliability Analysis system with the power of automatic knowledge acquisition and inconsistency checking, and more. To conclude our thesis, we propose an architecture of La MORA

Rethinking Assessment: Information Literacy Instruction and the ACRL Framework

Most information literacy instruction (ILI) done in academic libraries today is based on the ACRL’s Information Literacy Competency Standards for Higher Education, but with the replacement of these standards by the new Framework for Information Literacy for Higher Education, there is a need to re-evaluate current teaching strategies and instructional techniques so that they can better serve the Framework’s goals. This paper explores current trends in ILI instruction and in the area of assessment in particular, since ILI assessment provides an opportunity not only to evaluate teaching effectiveness but also to reinforce the learning goals of the new Framework itself. It proposes several ways that assessment strategies can be aligned with the goals of the Framework by using guided group discussion, online discussion platforms, and social media platforms, and proposes further avenues for research in the evaluation of such strategies