Welcome to Research Bank, our open research repository that includes research produced by students and staff while affiliated with Unitec, Eastern Institute of Technology (EIT), Otago Polytechnic, Toi Ohomai Institute of Technology and Southern Institute of Technology (SIT). It is intended to facilitate scholarly communication and shared access to our research outputs.
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Item A revision of the Coenogonium luteum (Coenogoniaceae) complex in Aotearoa | New Zealand, with new records and new species, and a note on C. tomentosum(National Academy of Sciences of Ukraine. M.G. Kholodny Institute of Botany, 2026-04-30)Coenogonium (lichenized Ascomycota: Coenogoniaceae) was last treated in Aotearoa | New Zealand by Galloway (2007), who accepted nine species, with a further species subsequently described, bringing the total to 10 species. Since this treatment, mounting evidence has indicated that Coenogonium luteum (Dicks.) Kalb & Lücking may constitute a species complex in New Zealand collections, highlighting the need for a comprehensive taxonomic re-evaluation. Specimens of C. luteum were examined from multiple New Zealand herbaria, with a focus on those from Auckland War Memorial Museum (AK), University of Otago (OTA) and Unitec (UNITEC). The results of this indicated that collections of C. luteum sensu lato included multiple taxa. Here, we present a revised circumscription of C. luteum for New Zealand material, report two new records for Aotearoa, C. australiense Kantvilas & Lücking and C. pineti (Ach.) Lücking & Lumbsch, and describe two new species: C. hepatiphilum C.J. James sp. nov. and C. goniocystosum C.J. James sp. nov. For all five species, we provide morphological descriptions, ecological notes, distribution data, conservation assessments and a revised key to Coenogonium in Aotearoa. In addition, we synonymize C. pertenue (Stirt.) Kalb & Lücking with C. luteum and C. tomentosum Müll. Arg. with C. implexum Nyl.Item A drone survey of a feral population of emu, Dromaius novaehollandiae (Latham, 1790), on Rēkohu / Wharekauri / Chatham Island, Chatham Islands(Royal Society of New Zealand Te Apārangi, 2026-02-04)Species monitoring and surveying is strongly limited by habitat accessibility. A feral population of emu (Dromaius novaehollan diae) established from five birds deliberately released on Rēkohu / Wharekauri / Chatham Island more than 30 years ago has not yet been quantitively assessed with respect to its population number and status. To address this issue, we conducted a short manual UAV (drone) survey on a portion of the area where this population is said to be concentrated. In total 303min of flight/survey time over 5 days (January 2025), we made 70 observations of emu, including 45 adults and 25 juveniles, with a calculated 13.5 emu observations per drone hour. The most observations in a single day were 28 individual birds; 17 adults and 11 juveniles. The largest flocks of emu were six individuals: three adults with three juveniles, and another flock of an adult with five juveniles. There is a need for a more extensive survey to estimate the total population size and a more detailed investi gation into the ecology of this population to ascertain the potential impact emu may have on the farmland and associated indig enous terrestrial ecosystems on Rēkohu. Emu have also been released in several locations in Aotearoa / New Zealand, and we advocate for similar studies thereItem Miss Honey meets AI: Reimagining reflective practice in ITE(2025-11)Why an AI Chatbot for formative feedback on reflections? Critical reflection is essential in initial teacher education because it empowers beginning teachers to “dig deeply into their practices,” enabling growth and readiness for the complexities of the profession (McLelland, 2024). Ross et al., (2024) suggest that shorter tasks with formative feedback gradually build reflective writing skills. Miss Honey supports an iterative process of writing and is available when the student is. What we have noticed: • Many students lack confidence to submit a draft • Miss Honey provides real time formative feedback • Variability in feedback across visiting lecturers Miss Honey aims to scaffold students thinking and provide equitable access to feedback while supporting academic staff to develop consistencyItem Miss Honey: Reimaging reflective practice in ITE(2026-02-10)DESIGN The proposed AI agent, Miss Honey, is designed to develop critical reflection skills during practicum placements by: • Supporting lecturers in providing constructive formative feedback. • Guiding students to improve reflective writing by evaluating uploaded reflections and prompting deeper critical thinking. KEY FUNCTIONS • Act as a mentor, analysing reflections section by section. • Encourage critical thinking, problem-solving, and linking theory to practice. • Promote use of the DATA Model and Te Whāriki framework. • Ensure APA referencing and proper structure without providing direct answersItem Utilizing artificial intelligence for website personality detection(2026)MAIN RESEARCH QUESTION: How can ML be used to automatically classify a website’s personality based on measurable quantitative attributes, without human subjective influence? RQ1: How can the ‘Items’ define in the WPS be systematically mapped to quantifiable website elements? RQ2: How can quantitative website elements be accurately extracted for personality classification? RQ3: How can ML modules be designed to classify website personality across multiple traits and dimensions? RQ4: How can the developed modules be validated against human perception of website personality? ABSTRACT To evaluate the personality of a website, surveys are commonly employed among individuals who have engaged with the respective website. However, surveys inherently introduce human bias due to the subjective nature of human input. The determination of a website's personality should ideally be objective and devoid of human bias and preferences. To achieve the classification of a website's personality without human intervention, this thesis proposes a methodology grounded in automated quantitative analysis. This method involves assigning ratings to specific quantitative features of a website and then using these ratings to assess personality traits. This research involves quantifying various elements of websites, utilizing a database comprising 3000 websites for algorithms training and testing. The data extraction tools i.e., JSoup, Selenium WebDriver, and IBM Tone Analyzer Service are employed to extract data from the websites. Artificial intelligence (AI) techniques have been utilized for gaining insight from the data collected, reducing the reliance on human intervention for data extraction processes. The integration of AI, including machine learning (ML) and natural language processing (NLP) as subsets, offers numerous enhancements to the data mining process. Four distinct ML algorithms are implemented to develop four modules by utilizing the acquired quantitative data from the websites. The chosen algorithms are K-means, Expectation Maximization (EM), Hierarchical Agglomerative Clustering (HAC), and Density-Based Spatial Clustering of Applications with Noise (DBSCAN ). Each of these algorithms is examined in terms of its methodology, applicability, and performance in organizing data into meaningful groups. The K-means algorithm partitions data based on centroid averages, requiring a predetermined number of clusters, while EM probabilistically assigns data points to clusters, accommodating various cluster shapes and sizes. HAC constructs a hierarchical structure of clusters through step-by-step merging or splitting, without prior knowledge of the number of clusters. DBSCAN identifies dense regions of data points separated by lower density areas, allowing for flexible cluster shapes and handling outliers effectively. Through this comparative analysis, insights into the strengths and limitations of each algorithm are studied. These four algorithms belong to four different clustering methods. Utilizing four algorithms from distinct clustering methods will yield varied website identification outcomes, bolstering confidence in the obtained results. The thesis includes the development of a software tool designed to streamline various stages of the research process, including the creation of the website database, extraction of quantitative data, application of ML techniques for calculations and modules development, maintain survey processing and analysis of the acquired results etc. The experiments are conducted individually for each module, utilizing identical training and testing datasets. A survey is then administered, and validation of the results obtained from the developed modules is carried out through this survey. Analysis of the experiment outcomes verifies that the developed module can accurately identify website personality with a success rate of up to 94% (with a Relative Error (Ratio) of ≤ 0.50), as validated by the validation dataset. Consequently, these modules enable the detection of a website's personality without relying on human input. This thesis discovers relationships between website attributes and website personality, presenting potential applications in various domains. Firstly, for example, website developers can utilize the insights gained from this research to design their websites in alignment with specific business requirements. By ensuring that the online portrayal of a brand resonates with its desired perception, developers can enhance customer perceptions and foster long term loyalty, crucial in today's digital landscape where authentic and engaging online experiences are sought after. Another possible application which is more relevant in today’s culture is the development of cultural websites that are aligned with New Zealand initiatives and movements, media, and the general interest of the public. This will serve as groundwork for individuals or organizations interested in creating diverse cultural platforms online. By providing insights into website attributes such as logos, imagery, content, and features, developers can leverage this research to craft culturally resonant websites that contribute to fostering cross-cultural understanding in our globalized digital world. This thesis is not only confined to the aforementioned general examples, but this thesis may also serve as a groundwork for further studies and disciplines, with broad applicability to various aspects of contemporary life.
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