Managing Educational Media at Scale:
Infrastructure for Monitoring and Organizing Online Video
Michael V. Miller and Anna S. CohenMiller
Abstract
As instructional materials increasingly circulate through internet-based platforms rather than formal publication channels, faculty face persistent challenges in sustaining informed engagement with such content over time. These challenges are often attributed to individual skill gaps or rapid technological change, but we argue that they reflect a deeper structural failure to support cumulative instructional practice under conditions of digital abundance. We introduce a framework that distinguishes among three interrelated but analytically distinct stages of instructional media engagement: discovery, ongoing monitoring, and long-term pedagogical organization (D–M–O). We show how these stages are routinely collapsed into within platform-centered search models, obscuring their differing infrastructural requirements and limiting instructors’ capacity to reuse and refine instructional resources across courses and semesters. Conceptually, the D–M–O distinction clarifies how instructors can move from episodic search toward cumulative practice by stabilizing the conditions under which materials can be retrieved for course preparation and applied in instruction. Using online collections of video as an illustrative case, we demonstrate how low-cost, faculty-managed monitoring and organizational infrastructures can support sustained current awareness, durable pedagogical memory, and instructional continuity without prescribing specific tools or platforms. Although developed in relation to instructional video, the D–M–O framework is intended to generalize to a wide range of internet-based instructional materials, offering a conceptual basis for understanding how higher education can better support teaching practice under conditions of persistent digital accumulation.
Acknowledgments
This article is conceptual and methodological in nature and does not report original research on human subjects. No new datasets were generated or analyzed for this study. AI-assisted tools were used to support editing for clarity and flow. The authors are solely responsible for the content of the article and its accuracy.
1. Introduction: The Structural Roots of Information Management Failure
Since 2010, recurring surveys administered by the first author in sociology courses have asked students from a wide range of majors and backgrounds two basic questions about their online practices: when you encounter valuable web content, how do you ensure that you can find it again, and when you identify a website or video channel that reliably produces useful material, how do you stay aware of new content from that source?
Although most students report high confidence in their ability to work effectively online, their responses reveal a persistent gap between perceived competence and actual practice. When asked how they preserve materials for later use, students commonly describe ad hoc strategies such as re-searching by title, bookmarking browser tabs, saving links locally, taking screenshots, or emailing links to themselves. These practices are widely acknowledged as fragmented and unreliable for supporting reuse over time. When asked how they monitor sources for new content, most report not monitoring them at all, or relying on memory and occasional manual checks.
This pattern—high confidence paired with ineffective practice—has remained stable across cohorts. Its persistence suggests a structural problem rather than an individual or generational one. If students, despite lifelong immersion in digital environments, continue to lack systematic approaches to preserving and monitoring online materials, there is little reason to assume that faculty have acquired such practices spontaneously. Research on information practices supports this conclusion: instructors rely on similar ad hoc strategies, including informal bookmarking, memory-based retrieval, and episodic searching (Jacques et al., 2021).
These findings run counter to a familiar assumption in higher education: that students, as so-called “digital natives,” possess intuitive mastery of online environments, while faculty lag behind due to later-life adoption (Prensky, 2001). This framing has been widely critiqued (Bennett et al., 2008; Kirschner & De Bruyckere, 2017). Empirical research consistently shows that students rely on episodic keyword searching, algorithmically ranked results, and informal saving practices that closely mirror those of their instructors (Head & Eisenberg, 2010, 2011). The issue, therefore, is not technological lag, but the absence of taught workflows for monitoring content sources, capturing pedagogically relevant materials, and maintaining retrievable collections over time (Jones, 2007, 2012; ACRL, 2016).
The significance of this gap has intensified as online instructional media have shifted from relative scarcity to persistent accumulation. Advances in digital production and distribution have enabled instructional materials—particularly video—to be created and shared at unprecedented scale (Burgess & Green, 2009). Platforms such as YouTube now host vast and continuously expanding repositories of instructional content. Materials that were once scarce and institutionally bound have become largely free, durable, and persistently available.
This transformation does not simply mean that more instructional material exists. Rather, it reflects a condition of ongoing accumulation in which content is produced continuously, remains accessible over time, and expands across semesters rather than being replaced. Under these conditions, the instructional challenge is no longer locating relevant material once, but sustaining informed engagement with growing repositories of content.
In this context, the ability to monitor instructional sources and organize selected materials becomes more than a matter of individual efficiency. These practices shape the resources that instructors encounter, retain, and integrate into their teaching over time. In their absence, instructional media use remains episodic, memory-dependent, and vulnerable to disruption; when supported, instructors can reuse vetted materials, preserve pedagogical context, and maintain continuity as curricula, platforms, and institutional conditions change. Monitoring and organization thus function as basic instructional infrastructures rather than optional enhancements.
It is this shift—from episodic scarcity to persistent accumulation—that motivates distinguishing among discovery, monitoring, and long-term organization as analytically distinct problems. Discovery, in this sense, is not simply a matter of locating material once, but reflects broader conditions of visibility that shape which instructional sources become known, which remain salient, and which disappear from view over time. Although often treated as a single activity within platform-centered environments, these practices unfold across different temporal horizons and pose distinct infrastructural demands.
The problem with platform-centered search is not only that it treats instructional media as something to be found once and then forgotten. It also shapes what remains visible over time. Content that is institutionally supported, professionally branded, or rewarded by engagement metrics is repeatedly surfaced, while pedagogically valuable sources that do not align with platform signals fade from view. As a result, instructors are pulled back into repeated searching—not because monitoring and organization lack value, but because platforms provide little support for keeping important sources visible and retrievable across time.
This article advances an analytic framework for understanding why higher education has struggled to sustain effective engagement with instructional media under conditions of digital abundance. We argue that these difficulties stem not from individual skill deficits or resistance to technology, but from a structural failure to distinguish among three distinct stages of instructional media engagement: discovery, ongoing monitoring, and long-term pedagogical organization.
We formalize this distinction as the Discovery–Monitoring–Organization (D–M–O) framework and show how each stage is routinely collapsed within platform-centered search and recommendation systems. Rather than proposing new tools or applications, our contribution lies in clarifying the infrastructural logic required to support cumulative teaching practice over time. Using instructional video repositories as a focal case, we illustrate how low-cost, faculty-managed monitoring and organizational infrastructures can enhance instructional durability, pedagogical continuity, and faculty agency across courses and semesters. Although developed for online video, the framework is intended to generalize to a wide range of internet-based materials circulating in contemporary higher education.
2. Personal Information Management and Educational Content
Research on personal information management (PIM) examines how individuals acquire, maintain, retrieve, and use information in their daily work (Jones, 2007, 2008). Across professional contexts, PIM studies consistently document difficulties in maintaining information over time, particularly when materials are distributed across multiple platforms, devices, and formats (Boardman & Sasse, 2004; Whittaker, 2011). These findings are directly relevant to instructional contexts, where instructors must manage large and continuously expanding bodies of digital content under conditions of persistence and accumulation.
Evidence that instructors and students lack systematic preparation for managing ongoing flows of instructional media is documented across PIM and related work. Studies repeatedly show a reliance on ad hoc practices, such as episodic searching, informal bookmarking, and memory-based retrieval, rather than explicit strategies for monitoring content sources or maintaining retrievable collections over time (Jones, 2007, 2008; Jacques et al., 2021). These patterns recur across professional and educational settings, suggesting that deficits are systemic rather than individual or cohort-specific (Whittaker, 2011). Rather than extending personal information management concepts into a new domain, this article treats instructional media curation as a distinct infrastructural problem shaped by pedagogical time horizons, disciplinary norms, and institutional conditions.
The distinction between discovery, monitoring, and organization has been recognized unevenly in prior work on current-awareness tools. Research in library and information science has examined how emerging web technologies reshape academic practices of staying informed, typically emphasizing tools and systems that surface new information or support personal collections rather than sustained instructional reuse (Tenopir et al., 2013; Bawden & Robinson, 2009; Case & Given, 2016).
For example, from a librarian's perspective, Mu (2008) identified RSS feeds and social bookmarking systems as valuable resources for managing new online information streams, treating them as complementary rather than unified practices. Mu and Kern (2011) later described leading workshops introducing these tools to faculty, demonstrating feasibility and institutional interest while framing adoption through episodic training rather than as an embedded, cumulative workflow.
Research on Personal Learning Environments (PLEs) and Personal Learning Networks (PLNs) has also long emphasized learner control over distributed digital tools, frequently citing RSS aggregation and social bookmarking as illustrative components of self-directed learning environments (e.g., Attwell, 2007; Downes, 2005; Drexler, 2010; Dabbagh & Kitsantas, 2012). In this literature, RSS is typically framed as a mechanism for accessing information streams, while social bookmarking is treated as a means of organizing and sharing resources. These tools, however, are generally discussed descriptively—as elements within a learner’s toolkit—rather than analytically, as distinct infrastructural responses to different stages of instructional engagement with expanding content streams. As a result, issues of sustained monitoring, cumulative organization, and pedagogical reuse over time have remained underspecified.
We build on this tradition but explicitly link monitoring and organizing into a unified, cumulative practice oriented toward long-term instructional use. Rather than treating RSS and social bookmarking as independent solutions, our framework integrates them into a faculty-managed knowledge infrastructure. In this formulation, “current awareness” is reconceptualized not as an episodic activity focused on discovery, but as an ongoing process that supports continuous monitoring, durable organization, and planned reuse of instructional media across courses and semesters.
3. From Individual Media to Repository-Level Thinking
Historically, film and multimedia curation in higher education has focused on individual artifacts such as feature films, documentaries, or isolated video clips selected for specific instructional moments. This item-level approach remains pedagogically valuable, particularly when instructors curate materials tightly aligned with specific course topics. However, it does not scale well under contemporary conditions in which instructional video content is produced continuously and made persistently available across multiple online platforms (Burgess & Green 2009; Cunningham & Craig 2019).
This shift requires a fundamental change in our unit of analysis: we must move from seeing video as a standalone identity to seeing it as a node within a sustained, repository-level infrastructure. For this purpose, we focus on online video repositories (OVRs): discrete, publicly accessible collections of videos that persist and grow over time. OVRs function less as static collections than as dynamic, accumulating archives (Lobato 2019). These repositories stream new materials without usually displacing older content, resulting in expanding media collections that persist across semesters.
Historically, institutionalized curation has emerged as a pragmatic response to such problems of informational abundance. In anthropology, the postwar expansion of ethnographic research prompted the creation of the Human Relations Area Files (founded in 1949) as a shared infrastructure for indexing and retrieval. A parallel dynamic later emerged in sociology when The Sociological Cinema (TSC) launched in 2010. In that early stage of online video, curation was necessarily an act of gathering one-off fragments—news stories, film clips, and documentaries—from a wide range of general-interest sites. Scholarly reflection during this era—exemplified by the focus on vetting individual fragments of found media (e.g., Andrist et al., 2014)—treated video as a singular pedagogical object rather than as a component of a greater whole.
The framework proposed here does not replace this curatorial impulse; rather, it extends it by providing the monitoring and organizational tools required to sustain engagement with a now-mature, repository-driven environment. Under contemporary conditions of rapid accumulation, the instructional challenge has shifted from "finding the clip" to "monitoring the source." Repository-level thinking reframes curation from a series of discrete selection decisions to an ongoing OVR management process. This shift moves discovery away from episodic encounter and toward the recognition of productive repositories over repeated item-level searching.
Much of this instructional content is currently hosted on YouTube. We treat YouTube not as a pedagogical model, but as the dominant infrastructural substrate that enables systematic, long-term monitoring via stable RSS feeds. While the present study focuses on OVRs as a primary case, this repository-level logic is fundamentally media-agnostic. Whether the source is a YouTube channel, a news section, or a podcast series, the goal remains the same: to move from episodic, search-based encounters to the sustained monitoring of productive, scholarly identities.
Managing such repositories requires different forms of support than working with individual files. Instructors must sustain awareness of new content, evaluate materials as repositories evolve, and organize selected items for reuse over time (Whittaker 2011; Jones 2012). Consistent with broader research on technology adoption, these challenges appear less related to initial motivation than to the availability of facilitating conditions—the infrastructural support—that enables continued use (Teo 2011).
The remainder of the article formalizes these challenges by distinguishing among Discovery, Ongoing Monitoring, and Long-term Pedagogical Organization as analytically distinct problems. We specify how low-cost workflows can support repository-level engagement, providing the downstream ability to retrieve materials efficiently during planning and apply them in contexts where time and learning objectives constrain what can realistically be used.
4. The Discovery, Monitoring, and Organization Problem
To address these multifaceted challenges, we distinguish among three analytically distinct but interrelated components of media engagement: discovery, ongoing monitoring, and long-term pedagogical organization (D–M–O). In practice, platform-centered search and recommendation systems, designed for episodic retrieval rather than sustained engagement, tend to collapse these distinctions. Under conditions of persistent growth in teaching-relevant media, this collapse becomes consequential, as instructors must locate new resources, remain aware of evolving repositories, and organize materials for future reuse (Jones, 2012; Whittaker, 2011). These challenges arise most sharply under conditions of repository-level accumulation, where instructional media is produced continuously and must be managed over time rather than located episodically.
Discovery (D) refers to the episodic identification of stable content repositories rather than individual items. Monitoring (M) denotes the ongoing, often automated maintenance of current awareness once repositories are known, shifting attention from memory-based checking to infrastructural support. Organization (O) involves the selective retention, annotation, and indexing of materials for long-term pedagogical reuse.
These components differ in their temporal structure. Discovery is contingent and irregular, whereas monitoring and organization are cumulative processes that unfold over time. By contrast, platform-centered search models collapse discovery, monitoring, and organization into episodic retrieval, thereby obscuring the infrastructural requirements of sustained instructional media management.
Although discovery, monitoring, and organization describe the infrastructural conditions under which instructional media can be accumulated and indexed over time, their pedagogical value is most fully realized through retrieval. Retrieval (R) involves locating already organized relevant materials under the temporal and cognitive constraints that characterize teaching practice, where decisions must often be made quickly and in relation to specific learning objectives, course modules, or conceptual frameworks.
Even well-organized collections can fail pedagogically if instructors cannot readily recall or locate materials when needed. In this sense, discovery, monitoring, and organization function not as ends in themselves, but as supports for reliable retrieval.
Retrieval alone, however, does not ensure instructional impact. The pedagogical significance of instructional media emerges through application—the integration of retrieved materials into explanation, discussion, illustration, or analytical practice within instructional settings. Application (A) transforms archived media into a didactic resource, enabling students to illustrate, contest, or render abstract concepts experientially visible. When media are successfully applied in the classroom, student responses often reinforce instructors’ judgments about teaching value, increasing the likelihood of future retrieval and reuse. In this way, discovery, monitoring, and organization support retrieval, while retrieval enables application, together forming a cumulative process through which media becomes incorporated into teaching practice over time.
Although this article is conceptual and methodological in orientation, its claims are grounded in systematic documentation of applied instructional media practices rather than abstract theorization alone. Specifically, our Discovery–Monitoring–Organization (D–M–O) framework is derived from and operationalized through sustained engagement with a real-world curation infrastructure for managing platform-based instructional videos over time. The appendices in this paper, therefore, function as repositories of empirical materials, documenting the selection criteria, monitoring routines, and organizational decisions through which the framework was enacted in practice. Rather than reporting interviews or surveys, the study offers practice-based grounding by making visible the infrastructural choices, disciplinary variation, and classificatory labor that structure how instructional media accumulates and is maintained within platform environments.
To illustrate how instructional videos accumulate differently across disciplinary contexts, Appendix A presents comparative repository-level starter collections in sociology and economics, demonstrating that discovery, monitoring, and organization pose distinct infrastructural challenges across fields. Appendix B then documents the RSS monitoring and social bookmarking workflow used to support these activities over time, detailing how discovery, ongoing awareness, and long-term pedagogical organization can be practically sustained under conditions of persistent digital accumulation. Together, these appendices document not only outcomes but the ongoing decision-making processes through which instructional media infrastructures are constructed and maintained.
4.1 Initial Discovery: Identifying Online Video Repositories
The rest of this section examines the components of the D–M–O framework in turn, beginning with initial discovery, the stage at which instructors first become aware that relevant OVRs exist. While discovery is the most visible point of engagement with instructional media, the central analytic contribution of the framework lies in distinguishing discovery from the cumulative work of ongoing monitoring and long-term pedagogical organization, which are taken up in subsequent sections. The analysis is framed at the level of the social sciences, though the underlying infrastructural issues extend across disciplines.
The first challenge instructors encounter is becoming aware that relevant OVRs exist, a task that is analytically distinct from locating individual videos for immediate classroom use. In principle, discovery may occur through multiple channels, including platform search, professional networks, syllabus circulation, disciplinary journals, curated resource lists, newsletters, and institutional or project-based aggregation efforts. OVR discovery involves identifying websites, channels, or collections that consistently distribute pedagogically relevant content over time, enabling instructional practice to move beyond episodic searching toward sustained engagement with productive creators and sources (Burgess & Green, 2009; Cunningham & Craig, 2019).
In practice, instructors typically rely on keyword searches through platforms such as Google or YouTube, which are optimized to surface individual items rather than stable collections. Search results are shaped by engagement metrics, personalization histories, and recency biases, privileging popular or entertaining clips while obscuring repositories that may have accumulated substantial instructional value but lack algorithmic prominence (Noble, 2018). As a result, discovery practices tend to favor short-term selection over long-term instructional planning.
Importantly, this article does not categorically reject algorithmic search or platform recommendations. Keyword searches and recommendation systems often play a crucial role in initial discovery, frequently leading instructors to usable individual videos. In many cases, it is precisely through such encounters that instructors first become aware of the existence, identity, and pedagogical orientation of an underlying OVR. Algorithmic search thus functions as a common entry point into repository-level engagement rather than as a comprehensive discovery solution.
The limitation of platform-centered search lies not in its ability to surface individual items, but in its lack of support for sustaining awareness of productive sources over time. Platform systems are designed to optimize immediate relevance and engagement, not long-term instructional memory. Content that is institutionally supported, professionally branded, or rewarded by platform metrics is repeatedly surfaced, while pedagogically valuable repositories that do not align with these signals fade from view. As a result, instructors are pulled back into repeated searching—not because monitoring and organization lack value, but because platforms provide little infrastructural support for keeping important sources visible, trackable, and retrievable across time.
This article does not propose a comprehensive method for OVR discovery, which varies substantially across disciplines and institutional contexts. Instead, it assumes that at least some repositories have already been identified—often through the very search practices described above—and focuses on the underexamined problem of sustaining engagement with those repositories over time through monitoring and long-term pedagogical organization.
4.2 Variability by Discipline
As noted, the OVR discovery problem is uneven across fields. Economics, for example, benefits from a strong tradition of public-facing explanation, more centralized teaching venues that highlight digital resources, and greater institutional visibility of educational content streams. Others, including Sociology, exhibit a mismatch between the volume of available repository-level content and the visibility of mechanisms that ensure those repositories are routinely accessible to instructors. This variability affects both the extent of work instructors must undertake to identify stable sources and their continued reliance on chance discovery, informal networks, or platform algorithms. In economics, discovery is often scaffolded by centralized journals, policy institutes, and well-resourced public-facing organizations, whereas in sociology, repository discovery more frequently depends on informal circulation, classroom spillover, and episodic encounter.
4.3 Distinguishing Discovery, Monitoring, and Organization
Most contemporary platforms subsume OVR discovery, monitoring, and organization within a single activity, typically labeled “search.” Keyword queries and algorithmic recommendation systems are designed to retrieve items on demand. Still, they offer limited support for the ongoing, cumulative work required to track and manage instructional materials over time. Even after instructors identify productive repositories, they frequently return to the discovery stage, forced to relocate materials rather than build durable instructional collections. When discovery is mediated primarily through platform visibility, instructors are repeatedly returned to the point of initial encounter rather than supported in maintaining stable relationships with sources over time.
This conflation has pedagogical and infrastructural consequences. OVR discovery is contingent and visibility-dependent, whereas monitoring and organization can be routinized once repositories are known. The framework proposed here explicitly separates these stages, focusing its intervention on monitoring and organization, activities that become increasingly consequential as instructional media persist and accumulate over time.
Although platform algorithms significantly shape what content is visible through search and recommendation, this article does not evaluate their design or bias. Instead, it examines how instructors can develop monitoring and organization practices that reduce reliance on opaque discovery systems once repositories have been identified.
4.4 Integrating Monitoring and Organization as Infrastructural Practice
The distinction between discovery, monitoring, and organization has been recognized unevenly in prior work on current-awareness tools. Research in library and information science has examined how emerging web technologies reshape academic practices of staying informed, often emphasizing tools that surface new information or support personal collections (Tenopir et al., 2013).
The present article builds on this tradition by explicitly linking monitoring and organization into a unified, cumulative practice oriented toward long-term instructional use. Rather than treating RSS and social bookmarking as independent solutions, the framework integrates them into a faculty-managed knowledge infrastructure. In this formulation, “current awareness” is reconceptualized not as an episodic activity focused on discovery, but as an ongoing process that supports continuous monitoring, durable organization, and selective reuse of instructional media across courses and semesters.
4.5 Scaling Discovery, Monitoring, and Organization Across Course Types
The demands associated with discovery, monitoring, and organization do not scale uniformly across instructional contexts. In particular, courses organized around substantive social phenomena place qualitatively greater pressure on monitoring and organizational infrastructures than discipline-centered courses, because relevant instructional media are produced continuously across multiple fields, platforms, and genres rather than within a bounded disciplinary ecosystem. As a result, the relative importance of monitoring and organization increases sharply in such courses.
In discipline-centered courses, discovery is typically front-loaded and convergent. Once a core set of discipline-relevant OVRs has been identified—often reflecting professional associations, established educators, or widely recognized explanatory channels—the marginal returns to continued discovery decline. Monitoring practices stabilize as instructors track a relatively small number of repositories with predictable publication rhythms, and organization can rely heavily on disciplinary categories that already structure the field’s intellectual terrain. While discovery, monitoring, and organization remain necessary, their scale and complexity are constrained by the coherence and relative stability of the discipline itself.
By contrast, courses organized around substantive problems, such as social stratification and race and ethnic relations, exhibit fundamentally different scaling dynamics. In such courses, relevant instructional media are produced across multiple disciplines beyond sociology (e.g., economics, political science, psychology), as well as in adjacent fields such as journalism, public policy analysis, data visualization, and documentary filmmaking. Discovery remains ongoing rather than convergent, as new repositories continually emerge that address inequality-related mechanisms, outcomes, and cases from diverse analytic vantage points. The instructional challenge is therefore not simply identifying high-quality materials, but sustaining awareness of a broad, heterogeneous, and continuously evolving media environment over time.
Substantive-topic courses are further complicated by a heightened degree of dynamism. Because they are organized around visible social structures and processes rather than disciplinary canons, their instructional relevance is directly shaped by ongoing social change. Shifts in political regimes, policy agendas, cultural narratives, and institutional power relations routinely generate new empirical cases, reframe existing inequalities, and alter the interpretive stakes of long-standing theoretical debates. Periods of intensified ideological polarization—such as the rise of authoritarian movements, expanding forms of political repression, and sustained attacks on concepts associated with diversity, equity, and inclusion—produce rapid changes in how stratification is experienced, justified, contested, and represented in public discourse. Under such conditions, instructional materials can become outdated not over decades, but over semesters.
These conditions place particular strain on monitoring practices. Substantive-topic courses often require instructors to track dozens of active repositories operating across multiple platforms, many of which respond directly to unfolding events rather than stable curricular calendars. Without dedicated monitoring infrastructure, the cognitive burden of keeping pace with such material becomes prohibitive.
RSS-based aggregation provides a means of externalizing this task, enabling instructors to maintain current awareness while decoupling attention from continual searching or reactive content acquisition. As monitored feeds accumulate over time, they also support longitudinal engagement with shifting narratives, policy developments, and explanatory frames surrounding the substantive topic.
Organization demands scale even more sharply in substantive-topic courses. Because disciplinary categories no longer provide a shared organizing logic, instructors must impose analytic structure themselves in order to support retrieval, comparison, and reuse across instructional contexts. Materials must be indexed according to pedagogically salient dimensions, such as level of analysis, theoretical orientation, empirical focus, political framing, or instructional purpose, rather than disciplinary provenance alone. In this context, social bookmarking systems function not merely as storage tools, but as mechanisms for constructing and maintaining instructor-defined analytic order across a growing and politically volatile corpus of instructional media.
Together, these contrasts highlight that the D–M–O framework is most consequential in instructional contexts where discovery remains open-ended, monitoring must respond to rapid economic and political change, and organizational labor cannot be delegated to disciplinary conventions. Substantive-topic courses therefore represent scaling-intensive cases in which monitoring and organization infrastructures are not ancillary conveniences but essential supports for sustained pedagogical engagement under conditions of historical flux. Rather than reflecting idiosyncratic over-curation, such practices respond directly to the structural conditions under which instructional media are produced, circulated, contested, and rendered pedagogically salient.
5. An Instructional Infrastructure for Monitoring and Organizing Educational Content
The discovery of high-quality OVRs is not primarily a technical problem that can be solved solely with software tools. It is shaped by disciplinary norms, institutional visibility, professional networks, and publication practices that vary widely across fields. Accordingly, our framework begins after relevant OVRs have been identified. This delimitation does not minimize the importance of discovery; rather, it reflects the fact that discovery is shaped by structural conditions of visibility that extend beyond the scope of individual workflow design. It instead addresses the later stages of ongoing monitoring and long-term organization through an integrated instructional workflow, which prior research has identified as conceptually and practically underdeveloped (Jones, 2012; Whittaker, 2011).
In this article, “workflow” refers to the temporal sequencing of discovery, monitoring, and organizing activities rather than to specific steps, tools, or interfaces. Framed in D–M–O terms, the intervention focuses primarily on the monitoring and organization stages that follow the identification of productive OVRs.
5.1 Clarifying the Scope of the Framework
This section clarifies the scope of that intervention and specifies the tasks the framework is designed to support. It does not replace discovery practices or instructor judgment. Instead, it provides infrastructural support for two recurring tasks once repositories are known: (a) maintaining awareness of newly published content and (b) organizing selected materials so they remain retrievable and reusable across courses and semesters. In pedagogical terms, these functions support the downstream ability to retrieve materials efficiently during planning and to apply them in teaching contexts where time, sequencing, and learning objectives constrain what can realistically be used. While discovery is episodic and contingent, monitoring and organization are cumulative by design. The framework supports these cumulative processes by shifting them from individual memory and ad hoc practice into stable technical systems.
5.2 Why RSS Monitoring and Social Bookmarking Work Together
RSS monitoring and social bookmarking address complementary dimensions of instructional media management that neither technology resolves independently. We argue that RSS monitoring supports ongoing awareness by allowing instructors to subscribe to updates from known repositories. Instead of manually checking multiple sources, instructors can review consolidated notifications as new material is published (Miller, 2011, 2016; Tenopir et al., 2013).
Social bookmarking, by contrast, supports long-term organization and retrieval. Beyond browser bookmarks or platform-based “save” functions, social bookmarking systems enable flexible tagging, brief annotations, and retrieval using multiple criteria, such as course, topic, theoretical orientation, or instructional purpose (Whittaker, 2011).
Prior work by the first author (Miller, 2011) suggested the value of linking content monitoring and retention tools into coordinated instructional workflows rather than treating them as independent practices. Building on this insight, we treat these technologies as components of a two-stage instructional infrastructure: RSS surfaces new content, while social bookmarking supports organization by indexing and retaining selected items with contextual metadata. This alignment reflects instructional time horizons in which monitoring is continuous, and organization is selective.
A central advantage of integrating monitoring and organization in this way is that the framework scales across different instructional time horizons and organizational levels without requiring changes in underlying infrastructure. We distinguish continuous awareness from selective curation: RSS monitoring operates continuously in the background, whereas organization occurs during periodic curation sessions, when instructors index and evaluate materials for future use. This separation enables sustained current awareness without requiring constant manual intervention.
Our framework also accommodates variation in scope and depth of engagement. Discovery efforts may range from identifying a small number of repositories for a specific course to monitoring hundreds of sources across an entire discipline. Similarly, organizational practices may involve minimal tagging for basic identification or more detailed pedagogical metadata to support retrieval across multiple criteria. Individual instructors may emphasize focused discovery through selective, in-depth indexing, whereas collaborative or departmental efforts may pursue broader discovery alongside shared organizational standards. In each case, the same monitoring and organizational infrastructure supports both targeted individual use and more comprehensive collective curation, allowing instructional media management to scale without increasing cognitive or procedural complexity.
5.3 From Reactive Searching to Cumulative Teaching Libraries
Our integrated framework shifts instructional media use from reactive searching toward cumulative resource development. Rather than repeatedly reconstructing instructional materials through keyword searches, instructors can build teaching libraries that grow over time and across courses. Each curated item retains contextual information—its location, relevance, and brief instructional notes—supporting retrieval under the temporal and cognitive constraints of course preparation rather than reconstruction through repeated searching. Over time, these accumulated annotations can reduce preparation costs, support reuse, and facilitate adaptation as courses, curricula, or institutional conditions change. In D–M–O terms, this shift enables reliable retrieval under instructional constraints, transforming media accumulation from a source of cognitive burden into a reusable pedagogical asset.
5.4 Technology-Agnostic Design and Durability
Because specific RSS readers and social bookmarking platforms may change, our framework is intentionally technology-agnostic. Its durability lies in the underlying logic—automated monitoring paired with structured organization—rather than in dependence on any particular application or service. Instructors can migrate between tools without abandoning accumulated teaching libraries or organizational schemes.
This design principle addresses a common barrier to adoption: skepticism rooted in prior experiences with discontinued or degraded educational technologies. By emphasizing infrastructural functions rather than branded solutions, the framework aligns with long-term instructional practice rather than short-lived platform cycles (Weller, 2020).
5.5 Translating Curation Infrastructure into Instructional Practice
Our framework does not require advanced technical expertise. Its value lies in formalizing practices that can be adopted incrementally and adapted to different instructional contexts.
Individual instructors may begin by identifying a small number of productive OVRs, establishing lightweight routines for monitoring new content, and selectively archiving materials for reuse. Over time, such practices will build teaching libraries within social bookmarking systems that preserve pedagogical context and enable cross-course reuse.
Faculty development initiatives can treat instructional media management as a skill rather than as an incidental activity. Workshops may help instructors distinguish between discovery, monitoring, and indexing, develop sustainable curation routines, and adopt tagging practices aligned with instructional goals, without prescribing specific tools. Whether such practices become durable is likely to depend on institutional support, shared conventions, and recognition of curation as instructional labor.
Institutions can support distributed curation through guidance, shared conventions, and stable resources, such as curated repository lists, shared tagging vocabularies, and interoperable tools.
In this sense, discovery, monitoring, and organization operate not as abstract principles but as practical infrastructures whose form, labor demands, and pedagogical consequences are shaped both by institutional support and by the disciplinary environments in which instructional media is produced and reused.
The appendices that follow extend the analytic framework developed in the main text through comparative, discipline-specific illustration. Appendix A presents parallel starter collections of online video repositories in sociology and economics, designed not as exhaustive inventories but as typological demonstrations of how instructional media accumulates under different disciplinary conditions. Read comparatively, these cases make visible the distinct production logics, authority structures, and pedagogical labor that shape problems of discovery, monitoring, and organization across fields. Appendix B documents the monitoring and organizational infrastructure used to sustain engagement with those OVRs over time. Together, these appendices render the D–M–O framework operationally explicit and empirically tractable by specifying observable practices, artifacts, and workflows, without themselves constituting an outcome-based evaluation of instructional effectiveness.
6. Conclusion: Curation as Pedagogical and Infrastructural Resilience
This article advances a comparative infrastructure framework for understanding the accumulation of instructional media across academic disciplines. Through parallel analyses of sociology and economics, we show that online video repositories embody distinct forms of pedagogical labor, authority, and scalability, producing discipline-specific challenges of discovery, monitoring, and organization. The D–M–O framework reframes instructional media engagement as an ongoing infrastructural practice rather than a series of isolated search decisions.
Over the past two decades, the expansion of online video has been enabled by broader technological changes in production and distribution (Burgess & Green, 2009; Weller, 2020). User-upload platforms such as YouTube have provided durable hosting, global distribution, and searchability for instructional content independent of institutional infrastructure, transforming instructionally relevant video from a scarce resource into an increasingly abundant one.
These changes have reshaped teaching practice. As distribution channels expanded, instructors became more willing to incorporate externally produced materials into lessons (Bennett et al., 2008; Kirkwood & Price, 2014). While this shift expands instructional possibilities, it also increases the volume of materials that could be monitored and organized over time.
Meanwhile, videos within many instructor-created online video repositories circulate in contexts with limited audience interaction, limited feedback, and few mechanisms that promote reuse beyond the originating course. Scalable curation infrastructures can increase visibility, selective reuse, and informal feedback, supporting instructional communities organized around shared topics or pedagogical approaches (Lobato, 2019; Palmer & Schueths, 2013). The relevance of these infrastructural conditions became especially visible during the rapid transition to remote teaching during the COVID-19 pandemic, which exposed vulnerabilities in practices reliant on episodic searching and individual memory (Fyfield et al., 2021; Nguyen & Palmer, 2024).
The framework we propose addresses general instructional fragility rather than exceptional circumstances, emphasizing the infrastructural conditions that shape how instructional media are encountered, retained, and reused over time. By foregrounding repository-level engagement, it supports pedagogical continuity by enabling instructors to draw on curated resources, coordinate informally around shared materials, and adapt under constraint (Jones, 2012; Whittaker, 2011).
As illustrated in Section 4.5, these infrastructural demands are most acute in substantive-topic courses, such as social stratification, where instructional relevance is continually reshaped by ongoing social, economic, and political change. In such contexts, monitoring and organization are not supplementary enhancements but central pedagogical capacities that enable instructors to sustain analytic coherence amid rapidly evolving empirical conditions. In this respect, instructional infrastructures that support discovery, monitoring, and organization enable instructors to continually connect individual experiences and public narratives to shifting contemporary conditions, sustaining pedagogical relevance as biographies and social structures evolve in real time.
At the same time, the pedagogical significance of these infrastructural practices lies in what they enable instructors to do within instructional contexts. Discovery, monitoring, and organization create the conditions under which instructors can reliably retrieve relevant materials during course preparation and apply those materials in explanation, illustration, and discussion. Without retrieval and pedagogical application, curation activity risks becoming an end in itself rather than a support for teaching practice. By lowering retrieval friction and stabilizing access to previously identified resources, D–M–O practices help ensure that instructional media can be integrated into teaching at the moment it becomes pedagogically useful.
Taken together, these processes form a broader instructional cycle that extends beyond discovery, monitoring, and organization. Discovery enables monitoring; monitoring supports organization; organization stabilizes retrieval; and retrieval makes pedagogical application possible. Over time, repeated cycles of retrieval and application feed back into organizational refinement, reinforcing the infrastructural conditions that support sustained instructional use. While this article centers on the D–M–O components of this cycle, its pedagogical significance is best understood in relation to this full Discovery–Monitoring–Organization–Retrieval–Application (DMORA) sequence.
Over time, repeated cycles of retrieval and application transform instructional media from isolated discoveries into durable components of instructional repertoires. Materials that prove effective in the classroom become easier to recall, locate, and reuse, reinforcing the organizational structures that made their retrieval possible. In this way, low-cost curation practices do more than manage informational abundance; they enable instructors to integrate continuously produced instructional media into stable teaching practice without requiring substantial technological infrastructure or institutional support.
Recent advances in artificial intelligence are likely to influence how instructors encounter, assess, and reuse instructional media. These developments, however, do not diminish the relevance of the infrastructural distinctions outlined here. Contemporary AI systems depend on structured inputs—stable content sources, accumulated materials, and durable metadata—to support tasks such as summarization, prioritization, and retrieval (Bender et al., 2021). As a result, the potential value of AI is greatest in contexts where discovery has already occurred and where monitoring and organization are sustained rather than episodic. Rather than collapsing discovery, monitoring, and organization into a single intelligent function, emerging AI tools are more likely to amplify the benefits of separating these stages, reducing the costs of ongoing engagement while leaving source selection and pedagogical judgment firmly in human hands.
The decision to adopt or not adopt systematic monitoring and organizing practices will shape how fully instructors can leverage the expanding array of online educational resources. In the absence of such practices, engagement with instructional media will remain episodic, limiting opportunities for cumulative refinement and reuse across courses and semesters. As a result, much of the instructional potential of internet-based content will remain only partially realized, not because relevant repositories are unavailable, but because they are not reliably monitored and organized over time.
Future research could extend this framework in several directions. Comparative studies might examine how D–M–O infrastructures operate across additional disciplines, institutional types, or national contexts. Longitudinal work could investigate how instructional repositories evolve over time, including how monitoring and organizational practices shape patterns of reuse, abandonment, or curricular integration. Finally, experimental and design-oriented studies could explore how emerging AI-assisted tools interact with existing monitoring and organizational infrastructures, clarifying when automation supports instructional judgment and when it risks reintroducing the very forms of opacity and collapse the framework seeks to avoid.
In sum, curation operates as pedagogical infrastructure. Rather than treating online video as static resources assembled during course preparation, curation-oriented practices position instructional media as evolving artifacts embedded in continuing instructional, organizational, and collegial activity across courses, semesters, institutions, and disciplines.
Although we have centered on video in this article, the D–M–O distinction and the infrastructural conditions that support it can be extended to a range of digital sites, including podcasts, data visualizations, interactive graphics, and text-based materials. Our contribution, therefore, lies not in optimizing video use per se, but in providing general-purpose infrastructural support for instructors seeking to exploit the educational potential of the internet under conditions of sustained content abundance.
References
ACRL. (2016). Framework for information literacy for higher education. Association of College and Research Libraries.
Bawden, D., & Robinson, L. (2009). The dark side of information: Overload, anxiety and other paradoxes and pathologies. Journal of Information Science, 35(2), 180–191. https://doi.org/10.1177/0165551508095781
Bender, E. M., Gebru, T., McMillan-Major, A., & Mitchell, M. (2021). On the dangers of stochastic parrots: Can language models be too big? Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 610–623.
Bennett, S., Maton, K., & Kervin, L. (2008). The “digital natives” debate: A critical review of the evidence. British Journal of Educational Technology, 39(5), 775–786. https://doi.org/10.1111/j.1467-8535.2007.00793.x
Boardman, R., & Sasse, M. A. (2004). “Stuff goes into the computer and doesn’t come out”: A cross-tool study of personal information management. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 583–590). ACM. https://doi.org/10.1145/985692.985766
Burgess, J., & Green, J. (2009). YouTube: Online video and participatory culture. Polity Press.
Case, D. O., & Given, L. M. (2016). Looking for information: A survey of research on information seeking, needs, and behavior (4th ed.). Emerald Group Publishing.
Cunningham, S., & Craig, D. (2019). Social media entertainment: The new intersection of Hollywood and Silicon Valley. NYU Press.
Fyfield, M., Henderson, M., Heinrich, E., & Redmond, P. (2021). Online professional learning communities: A COVID-19 legacy? Australasian Journal of Educational Technology, 37(4), 1–16. https://doi.org/10.14742/ajet.6856
Head, A. J., & Eisenberg, M. B. (2010). Truth be told: How college students evaluate and use information in the digital age. Project Information Literacy.
Head, A. J., & Eisenberg, M. B. (2011). How college students use the web to conduct everyday life research. First Monday, 16(4). https://doi.org/10.5210/fm.v16i4.3484
Jacques, J., et al. (2021). (As cited).
Note: The manuscript cites Jacques et al. (2021) without a full title. You will want to confirm and complete this reference before submission.
Jones, W. (2007). Keeping found things found: The study and practice of personal information management. Morgan Kaufmann.
Jones, W. (2008). Personal information management. Annual Review of Information Science and Technology, 41, 453–504. https://doi.org/10.1002/aris.2007.1440410117
Jones, W. (2012). No knowledge lost: The science of personal information management. Oxford University Press.
Kirkwood, A., & Price, L. (2014). Technology-enhanced learning and teaching in higher education: What is “enhanced” and how do we know? A critical literature review. Learning, Media and Technology, 39(1), 6–36. https://doi.org/10.1080/17439884.2013.770404
Kirschner, P. A., & De Bruyckere, P. (2017). The myths of the digital native and the multitasker. Teaching and Teacher Education, 67, 135–142. https://doi.org/10.1016/j.tate.2017.06.001
Lobato, R. (2019). Netflix nations: The geography of digital distribution. NYU Press.
Miller, M.V. (2011). A system for integrating online multimedia into college curriculum. MERLOT Journal of Online Learning and Teaching, 7(2), 1-19. http://jolt.merlot.org/vol7no2/miller_0611.htm
Miller, M.V. (2016). Accessing emergent online content via RSS. In M. Wray, Daniels, J, Fetner, T., (eds.) Promoting Sociological Research: A Toolkit. Washington, DC: American Sociological Association. http://www.asanet.org/sites/default/files/savvy/documents/ASA/pdfs/Promoting_Sociological_Research_Toolkit.pdf
Miller, M.V. & CohenMiller, A.S. (2019). Open video repositories for college instruction: A guide to the social sciences. Online Learning, 23, 2. https://olj.onlinelearningconsortium.org/index.php/olj/article/view/1492.
Mu, C. (2008). RSS feeds and social bookmarking in library services. Reference Services Review, 36(4), 396–408. https://doi.org/10.1108/00907320810920355
Mu, C., & Kern, M. (2011). Teaching information literacy using social media. Journal of Information Literacy, 5(2), 21–35.
Nguyen, T., & Palmer, S. (2024). (As cited).
Note: Please verify final publication details; appears to be a recent post-COVID higher education study.
Noble, S. U. (2018). Algorithms of oppression: How search engines reinforce racism. NYU Press.
Palmer, S., & Schueths, A. (2013). Online communities and informal learning. Journal of Educational Technology & Society, 16(2), 173–186.
Prensky, M. (2001). Digital natives, digital immigrants. On the Horizon, 9(5), 1–6. https://doi.org/10.1108/10748120110424816
Tenopir, C., Volentine, R., & King, D. W. (2013). Social media and scholarly reading. Online Information Review, 37(2), 193–216. 8
Weller, M. (2020). 25 years of ed tech. Athabasca University Press.
Whittaker, S. (2011). Personal information management: From information consumption to curation. Annual Review of Information Science and Technology, 45, 1–62. https://doi.org/10.1002/aris.2011.1440450101