Supporting the Discoverability of Open Educational Resources: on the Scent of a Hidden Treasury

Open Educational Resources (OERs), now available in large numbers, have a considerable potential to improve many aspects of society, yet one of the factors limiting this positive impact is the difficulty to discover them. This thesis investigates and proposes strategies to better support educators in discovering OERs. The literature suggests that the effectiveness of existing search systems, including for OER discovery, could be improved by supporting users, such as teachers, in carrying out more exploratory search activities closer to their existing methods of working. Hence, a preliminary taxonomy of OER-related search tasks was produced, based on an analysis of the literature, interpreted through Information Foraging Theory. This taxonomy was empirically evaluated to preliminarily identify a set of search tasks that involve finding other OERs similar to one that has already been identified, a process that is generally referred to as Query By Example (QBE). Following the Design Science Research methodology, three prototypes to support as well as to refine those tasks were iteratively designed, implemented, and evaluated involving an increasing number of educators in usability oriented studies. The resulting high-level and domain-oriented blended search/recommendation strategy transparently replicates Google searches in specialized networks, and identifies similar resources with a QBE strategy. It makes use of a domain-oriented similarity metric based on shared alignments to educational standards, and clusters results in expandable classes of comparable degrees of similarity. The summative evaluation shows that educators do appreciate this strategy because it is exploratory and – balancing similarity and diversity – it supports their high-level tasks, such as lesson planning and personalization of education. Finally, potential barriers and opportunities for the uptake of OER discovery tools were investigated in a structured interview study with experts from the OER field. Identified issues included how to work across multiple OER portals, variability in the use of metadata and how to align with the working practices of teachers. The findings of the thesis can be used to inform the research and development of methods and tools for OER discovery as well as their deployment to serve the needs of educators

Supporting the discoverability of open educational resources

Open Educational Resources (OERs), now available in large numbers, have a considerable potential to improve many aspects of society, yet one of the factors limiting this positive impact is the difficulty to discover them. This study investigates and proposes strategies to better support educators in discovering OERs, mainly focusing on secondary education. The literature suggests that the effectiveness of existing search systems could be improved by supporting high-level and domain-oriented tasks. Hence a preliminary taxonomy of discovery-related tasks was developed, based on the analysis of the literature, interpreted through Information Foraging Theory. This taxonomy was empirically evaluated with a few experienced educators, to preliminary identify an interesting class of Query By Examples (QBE) expansion by similarity tasks, which avoids the need to decompose natural high-level tasks in a complex sequence of sub-tasks. Following the Design Science Research methodology, three prototypes to support as well as to refine those tasks were iteratively designed, implemented, and evaluated involving an increasing number of educators in usability oriented studies. The resulting high-level and domain-oriented blended search/recommendation strategy, transparently replicates Google searches in specialized networks, and identifies similar resources with a QBE strategy. It makes use of a domain-oriented similarity metric based on shared schema.org/LRMI alignments to educational frameworks, and clusters results in expandable classes of comparable degree of similarity. The summative evaluation shows that educators appreciate this exploratory-oriented strategy because – balancing similarity and diversity – it supports their high-level tasks, such as lesson planning and personalization of education

Breakthrough Cancer Pain: Preliminary Data of The Italian Oncologic Pain Multisetting Multicentric Survey (IOPS-MS)

Introduction: An ongoing national multicenter survey [Italian Oncologic Pain multiSetting Multicentric Survey (IOPS-MS)] is evaluating the characteristics of breakthrough cancer pain (BTP) in different clinical settings. Preliminary data from the first 1500 cancer patients with BTP enrolled in this study are presented here. Methods: Thirty-two clinical centers are involved in the survey. A diagnosis of BTP was performed by a standard algorithm. Epidemiological data, Karnofsky index, stage of disease, presence and sites of metastases, ongoing oncologic treatment, and characteristics of background pain and BTP and their treatments were recorded. Background pain and BTP intensity were measured. Patients were also questioned about BTP predictability, BTP onset (≤10 or >10 min), BTP duration, background and BTP medications and their doses, time to meaningful pain relief after BTP medication, and satisfaction with BTP medication. The occurrence of adverse reactions was also assessed, as well as mucosal toxicity. Results: Background pain was well controlled with opioid treatment (numerical rating scale 3.0 ± 1.1). Patients reported 2.5 ± 1.6 BTP episodes/day with a mean intensity of 7.5 ± 1.4 and duration of 43 ± 40 min; 977 patients (65.1%) reported non-predictable BTP, and 1076 patients (71.7%) reported a rapid onset of BTP (≤10 min). Higher patient satisfaction was reported by patients treated with fast onset opioids. Conclusions: These preliminary data underline that the standard algorithm used is a valid tool for a proper diagnosis of BTP in cancer patients. Moreover, rapid relief of pain is crucial for patients’ satisfaction. The final IOPS-MS data are necessary to understand relationships between BTP characteristics and other clinical variables in oncologic patients. Funding: Molteni Farmaceutici, Italy

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population