Doctor of Philosophy (Ph.D.)

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  • Publication
    Open Access
    A multiple-case study on school support systems for low-performing primary students of Chinese language
    (2024)
    Chau, Sook Kuan

    Bilingual education has always been a cornerstone of Singapore’s education. Chinese Language (CL) is offered as a compulsory Mother Tongue Language (MTL) subject in all Singapore mainstream schools to students of Chinese ethnicity. With the intergenerational change of home language environment and increasingly diversified profile of CL students, supporting low-performing students has become an area of concern in the teaching of CL. In response, the Ministry of Education (MOE) implemented initiatives such as the Chinese Language Modular Curriculum in 2007 for Primary 2 to 6 levels and the Mother Tongue Support Programme (MTSP) in 2021 for Primary 3 and 4 levels. Yet, even with these initiatives, a structured learning support programme for lower primary low-performing students seems lacking, schools are expected to exercise their own discretion on how to customise intervention practices and support programmes for Primary 1 and 2 low-performing students of CL, and students excluded from the MTSP.

    Therefore, this study aims to gain a deep understanding on how schools customise school-based support systems for the learning of low-performing students of CL, and to provide an in-depth description regarding the good practices that work together to create conducive conditions for the learning and development for these students.

    To define good practices, this study uses a theoretical perspective based on Deci and Ryan’s self-determination theory (SDT) (1985, 2004) to discuss the need-supportive and need-thwarting factors within the schools practices. SDT postulates that humans are inherently motivated to learn and internalise knowledge, and this motivation will be fostered and sustained by supporting the basic psychological needs for autonomy, competence and relatedness. This study uses a multiple-case study design to answer two research questions:

    1) How do schools support the learning of low-performing students of Chinese Language? What models, approaches, and strategies do schools/teachers use?

    2) How do these models, approaches, and strategies support the psychological needs of low-performing students of Chinese Language? Why?

    This study collects and analyses interview and observational data from three participating schools, elaborates on (i) the details of school support systems, focusing on conceptualisation, implementation, effectiveness and limitations of the various components of the systems, highlighting similarities and differences in several common procedural steps, including considerations on strengthening students' learning attributes, identification of low-performing students, deployment of teachers, and practices adopted by teachers in the classroom; (ii) how these nuances impact the support of the basic psychological needs of low-performing CL students, detailing the common need-supportive and need-thwarting factors and discussing their impacts.

    This study provides a rich repertoire of data for school leaders, teachers and researchers seeking insights into the elements of an effective support system for low-performing students in Mother Tongue Languages and other subjects. Future studies can replicate this research across different levels, subjects, and school settings, and further empirical studies employing alternative measures can be conducted to assess the impact of each classroom condition and teacher behaviour on the psychological needs and motivation of low-performing students, providing a more substantive dimensions to the findings and phenomenon discussed in this study.

      6  245
  • Publication
    Open Access
    Neuromorphic vision sensors for computer vision
    (2024)
    Can, Cuhadar
    There have been significant advancements in the field of artificial intelligence (AI) over the past two decades, allowing such technologies to acquire popularity in both industry and academia. Face recognition software on Facebook or the iPhone, self-driving cars, and image recognition software are examples of AI applications that have become more prevalent in our daily lives. Computer vision, which is the study of enabling machines to gain a high-level understanding of images, such as pattern or object recognition, is a subfield of AI. Consequently, computer vision research has acquired significant importance. Convolutional neural networks (CNN) have garnered a great deal of interest due to their exceptional performance in image classification. Due to the computer's hardware limitations for self-learning and parallel computing, even the most advanced software is presently incapable of imbuing machines with human cognitive skills. Despite the progress made in computer vision, there are still problems to be resolved. One challenge is object recognition under varying illumination conditions. In particular, changes in illumination conditions can contaminate CNN's image segmentation, leading to erroneous object detection. Even though this issue can be mitigated by using a larger CNN training set, the enormous computational and energy resources required to continuously execute CNN for always-on applications, such as surveillance or self-navigation, pose a significant challenge for battery-dependent mobile systems. To address this age-old issue, a novel optoelectronic sensor capable of automatically compensating for sudden variations in light exposure is demonstrated in this thesis, without the need for sophisticated object detection software. With this method, effective fault-tolerant object detection may be developed with little training data, low energy consumption, and low computational expenses. Another prominent issue in computer vision is occlusion, which occurs when an object's key features momentarily vanish behind another body, making image detection difficult for the computer. While the human brain is capable of compensating for the portions of a blocked object that are not visible, computers lack these scene interpretation skills. Typically, cloud computing with convolutional neural networks is the preferred method for managing such a scenario. However, cloud computing should be minimized for mobile applications where energy consumption and computational costs are crucial. In this regard, a novel computer vision sensor that can effectively detect and track covered objects on a hardware level without relying heavily on occlusion management software is proposed. The underlying mechanism that alloy the emergence of these smart optoelectronic sensors will be discussed in detail in this thesis, laying the groundwork for the potential development of new a new generation of edge-computing cameras that allow computer vision applications to be carried out in a more energy- and computationally-efficient way.
      22  309
  • Publication
    Open Access
    On the processes of songwriting : a case study of popular music songwriters in Singapore
    (2024)
    Chong, Soon Khong

    Music composing has been regarded to lie at the heart of music pedagogy (e.g., Winters, 2012) as it has been argued to underpin the development of musical skills and understanding (Glover, 2002; Odam, 1995; Paynter, 1982). P. R. Webster (2013) went as far as to say that music composing increases musical intelligence. Music composing has also been argued to promote the development of imagination, inventiveness, and creativity (Paynter, 2000; P. R. Webster, 2013). Additionally, music composing promotes agency development (Cape, 2014; Mantie, 2008). Moreover, music composing (particularly songwriting) has been shown to contribute to mental health (Baker, 2016; Baker et al., 2009; Dalton & Krout, 2006; Kinney, 2012; Kumm, 2013; Palidofsky & Stolbach, 2012; Rio & Tenney, 2002; Silverman, 2013; Wolf & Wolf, 2012). Finally, music composing contributes towards national economy when individuals become professional music composers in the realm of popular music.

    Despite these benefits, music composing is insufficiently taught in schools (e.g., Hogenes et al., 2015; Juntunen, 2011; Lum et al., 2014; Makris et al., 2022; Menard, 2015; Suomi et al., 2022; Westerlund & Partti, 2013) due to a lack of teaching confidence and know-how among other reasons (C. Byrne & Sheridan, 1998; Lum & Dairianathan, 2014; Strand, 2006; Westerlund & Partti, 2013; Winters, 2012). The manner in which the subject is taught is also a cause for concern for it tends to focus on procedural aspects rather than creativity (Wise, 2016). Additionally, there have been advocacies for more use of popular music in general music education to bridge the gap between what students enjoy outside schools versus what is taught in schools (Colquhoun, 2018; Dimitriadis, 2009; Ng, 2018).

    To help address the above concerns and to inform pedagogy, the present case study examined the lifelong learning and music-songwriting processes of five professional popular music composers (including me as one of the participants) in Singapore. The specific research questions for the present study are: (a) What are the thinking processes of professional music-songwriters when composing popular music? (b) How are lived experiences, attitudes towards music, beliefs or anything else involved when professional music-songwriters compose popular music? (c) How do professional music-songwriters learn to compose popular music? The study involves two components: (a) narrative biography; and (b) music-songwriting task. For the latter, the Stimulated Recall (STR) method (Burden et al., 2015; Calderhead, 1981; Collins, 2005, 2007; Lyle, 2003; Pohjannoro, 2014, 2016) was used. Data collected consists of interviews and autobiography (for me as participant) as well as artifacts (Musical Instrument Digital Interface [MIDI] files, audio files and Digital Audio Workstation [DAW] session files) as stimuli for the STR method. Dual Process Theory (DPT) which attributes human information processing to System 1 (S1) and System 2 (S2) thinking modes (Frankish & Evans, 2009) was adopted to underpin the present study.

    Themes emerged from the data of the present study include: (a) Music songwriters employed S1-S2 synergy with agility for creativity; (b) music-songwriters employed imagination and adaptation to create novelty; (c) music-songwriters worked under constraints and trade-offs defined by client specifications, design integrity and music theory compliance; (d) music-songwriters considered affect as an impetus for music-songwriting; (e) music-songwriters adopted composing strategies often involving digital technology; (f) music-songwriters learned through lifelong engagement in a wide range of musical activities; and (g) learning motivation of music-songwriters was contingent on five social factors.

    The present study is novel in that by studying both the composing and learning processes in a single study, it established the relationship between the modes of listening (distracted, attentive and purposive) during learning and the modes of thinking (S1 and S2 according to DPT) during music-songwriting. Findings from the present study implicate the need for teachers to perform two roles: (a) to help learners build a foundation for learning music-songwriting; and (b) to facilitate the process of music songwriting.

      99  342
  • Publication
    Open Access
    Proof and proving in the Singapore secondary school mathematics curriculum
    (2023)
    Navinesh Thanabalasingam

    A mathematical proof is an unbroken sequence of steps that establish a necessary conclusion based on truth preserving rules of logic. However, in practice it may be a series of ideas and insights rather a sequence of formal steps. It has been a common belief that this abstract concept is out of reach to students and even some teachers and hence not the focus of the general mathematics curriculum.

    This study treats proof in a broader sense, recognising that a narrow view of proof neither reflects mathematical practice nor offers the greatest opportunities for promoting mathematical understanding. It explores proof and its aspects, proof and its place in the curriculum, students’ and teacher’s conceptions and beliefs about proof in the context of the Singapore mathematics curriculum in secondary schools.

    Two teachers and four students from their respective classes in a secondary school in Singapore participated in the study that was carried out in three phases. In the first phase all the subjects (both teachers and students) did a questionnaire (conceptions) comprising modified secondary four national examination questions on mathematics (elementary and additional mathematics). In the second phase the teachers did a survey (beliefs) on their beliefs about teaching proofs while the students did the same about their beliefs of learning proofs. In the third phase, based on the data from the first two phases (conceptions and beliefs), subjects were interviewed for clarifications and further elaborations.

    The findings related to curricular materials show that both Elementary Mathematics (EM) and Additionally Mathematics (AM) textbooks are structurally similar in terms of the proportion and type of proof tasks available. There is a higher concentration of proof tasks in the AM textbook compared to the EM textbook, suggesting a possible bias towards AM in containing proof tasks. Most proofs were found in the Geometry strand for both textbooks, suggesting a possible bias towards Geometry in containing proof tasks. There is a lack of variety of proof tasks in both the textbooks. Regarding teachers' conceptions related to teaching proof, it was found that there is diversity and depth of proof strategies used by teachers. Also, teachers' conceptions of proof were heavily influenced by their own mathematical knowledge and understanding of concepts and theorems. Students mainly perceived proofs as difficult problems to work on. Challenges related to the learning of proofs, stemmed from textbooks and school notes lacking in clarity and articulation using complex language.

      39  188