Et sted å starte: Geografiske utforskninger av litteratur

The article is a reflection over an experimental teaching sequence with students in Norwegian L1, autumn 2020. Departing from the field of literary geographies, we used geography as an analytical lens when reading the Swedish children's novel, The Murderer's Ape by Jakob Wegelius (2014). Our students mapped the geographical places in the novel on Padlet, they analyzed the visual maps included in the endpapers and discussed central settings in the novel. The experiment indicates that this analytic lens helps the students to read analytically, and it encourages critical reflections. However, we have to work more with enhancing close reading techniques. The teaching sequence was experimental and a part of a series of geographic explorations that aims at developing a geographical literary didactic. This didactic is meant to answer a problem posed by the new national curriculum, LK20: How can we enhance critical reading through explorative, cross disciplinary work with literature?Artikkelen tar form som en refleksjon over et utprøvende undervisningsopplegg med studenter i norskdidaktikk, høsten 2020. Med utgangspunkt i teorifeltet litterære geografier brukte vi geografi som analytisk linse i arbeidet med den svenske barneromanen Mördarens apa av Jakob Wegelius (2014). Studentene kartla romanens geografiske steder på et kart i Padlet, de analyserte de visuelle kartene i innsidepermene og reflekterte over sentrale handlingssteder i romanen. Utprøvingen indikerer at denne analytiske tilnærmingen hjalp studentene med å lese analytisk og stimulerte til kritiske refleksjoner. Likevel må det arbeides videre med å stimulere til nærlesing. Undervisningssekvensen er en del av en serie geografiske utprøvinger med det formålet å utvikle en spatial litteraturdidaktikk. Denne didaktikken skal svare på en utfordring i den nye læreplanen, LK20, nemlig: Hvordan kan vi utvikle kritisk lesing gjennom utforskende og tverrfaglig arbeid med skjønnlitteratur

Using Natural Language Processing to Organize and Analyze Oral History Projects

In this paper, I discuss how Natural Language Processing (NLP) tools, particularly large language models (LLMs) and topic modeling, can be employed to organize and analyze large-scale oral history projects. To illustrate their utility, I demonstrate two use cases with the Ellis Island Oral History Project: metadata mining and topic assignment. Subsequently, I use the outputs from these exercises to explore two research questions. Keywords: natural language processing, artificial intelligence, archives, immigratio

Close and Distant Reading Visualizations for the Comparative Analysis of Digital Humanities Data

Traditionally, humanities scholars carrying out research on a specific or on multiple literary work(s) are interested in the analysis of related texts or text passages. But the digital age has opened possibilities for scholars to enhance their traditional workflows. Enabled by digitization projects, humanities scholars can nowadays reach a large number of digitized texts through web portals such as Google Books or Internet Archive. Digital editions exist also for ancient texts; notable examples are PHI Latin Texts and the Perseus Digital Library. This shift from reading a single book “on paper” to the possibility of browsing many digital texts is one of the origins and principal pillars of the digital humanities domain, which helps developing solutions to handle vast amounts of cultural heritage data – text being the main data type. In contrast to the traditional methods, the digital humanities allow to pose new research questions on cultural heritage datasets. Some of these questions can be answered with existent algorithms and tools provided by the computer science domain, but for other humanities questions scholars need to formulate new methods in collaboration with computer scientists. Developed in the late 1980s, the digital humanities primarily focused on designing standards to represent cultural heritage data such as the Text Encoding Initiative (TEI) for texts, and to aggregate, digitize and deliver data. In the last years, visualization techniques have gained more and more importance when it comes to analyzing data. For example, Saito introduced her 2010 digital humanities conference paper with: “In recent years, people have tended to be overwhelmed by a vast amount of information in various contexts. Therefore, arguments about ’Information Visualization’ as a method to make information easy to comprehend are more than understandable.” A major impulse for this trend was given by Franco Moretti. In 2005, he published the book “Graphs, Maps, Trees”, in which he proposes so-called distant reading approaches for textual data that steer the traditional way of approaching literature towards a completely new direction. Instead of reading texts in the traditional way – so-called close reading –, he invites to count, to graph and to map them. In other words, to visualize them. This dissertation presents novel close and distant reading visualization techniques for hitherto unsolved problems. Appropriate visualization techniques have been applied to support basic tasks, e.g., visualizing geospatial metadata to analyze the geographical distribution of cultural heritage data items or using tag clouds to illustrate textual statistics of a historical corpus. In contrast, this dissertation focuses on developing information visualization and visual analytics methods that support investigating research questions that require the comparative analysis of various digital humanities datasets. We first take a look at the state-of-the-art of existing close and distant reading visualizations that have been developed to support humanities scholars working with literary texts. We thereby provide a taxonomy of visualization methods applied to show various aspects of the underlying digital humanities data. We point out open challenges and we present our visualizations designed to support humanities scholars in comparatively analyzing historical datasets. In short, we present (1) GeoTemCo for the comparative visualization of geospatial-temporal data, (2) the two tag cloud designs TagPies and TagSpheres that comparatively visualize faceted textual summaries, (3) TextReuseGrid and TextReuseBrowser to explore re-used text passages among the texts of a corpus, (4) TRAViz for the visualization of textual variation between multiple text editions, and (5) the visual analytics system MusikerProfiling to detect similar musicians to a given musician of interest. Finally, we summarize our and the collaboration experiences of other visualization researchers to emphasize the ingredients required for a successful project in the digital humanities, and we take a look at future challenges in that research field

COMMUNITY COLLEGE CHOICE AND CAMPUS EXPERIENCES OF HIGHLY QUALIFIED STUDENTS

The design of higher education is a stratified system to funnel the most academically prepared students from the highest earning households to the most selective higher education institutions. Conversely, students who are the least academically prepared and in the lowest socio-economic quintiles are funneled to the lowest-tiered institution in alarming proportions. The undermatch hypothesis concludes that a student who qualifies for admissions to a research university or a regionally accredited university will have a higher propensity to graduate if they are appropriately matched (Bowen et al., 2009). As Bourdieu (1977) argues, the education system is the structure that ensures the continuous oppression of the lower quintiles of social class, supports the power relations, and favors the dominant culture. The messiness of choice is complex when considering merits, college options, degree choices, location, housing, cost, family expectations, and an array of other factors that play a part in the final outcome of where to begin college. The study will highlight the process as the highly qualified student approaches college choice and decides to begin at an open access community college. The longitudinal research will then explore the experience of highly qualified students at a community college, adding to the literature