Artificial Intelligence and Education. Guidance for Policy-makers

Artificial Intelligence (AI) has the potential to address some of the biggest challenges in education today, innovate teaching and learning practices, and ultimately accelerate the progress towards SDG 4. However, these rapid technological developments inevitably bring multiple risks and challenges, which have so far outpaced policy debates and regulatory frameworks. This publication offers guidance for policy-makers on how best to leverage the opportunities and address the risks, presented by the growing connection between AI and education. It starts with the essentials of AI: definitions, techniques and technologies. It continues with a detailed analysis of the emerging trends and implications of AI for teaching and learning, including how we can ensure the ethical, inclusive and equitable use of AI in education, how education can prepare humans to live and work with AI, and how AI can be applied to enhance education. It finally introduces the challenges of harnessing AI to achieve SDG 4 and offers concrete actionable recommendations for policy-makers to plan policies and programmes for local contexts

Beyond disruption: technology enabled learning futures; 2020 edition of Mobile Learning Week, 12-14 October 2020 : report

Mobile Learning Week (MLW) is the United Nations’ flagship event on Information and Communication Technology (ICT) in education, and has been organized by UNESCO and its partners consecutively for eight years. The 2020 edition of MLW 2020, held online because of the COVID-19 pandemic, was devoted to the theme of Beyond Disruption: Technology Enabled Learning Futures. The three-day event focused on knowledge sharing on the use of technology to ensure learning continuity and quality, and to build resilient education systems against the backdrop of the COVID-19 education disruption. This synthesis report consolidates, showcases and assesses lessons learned from distance learning programmes shared by more than 3,000 live online participants and 90 speakers, including ministers, representatives from governmental agencies of Member States and international organizations, together with experts from NGOs, the private sector, as well as academic institutes

Using Exploratory Factor Analysis for Locating Invariant Referents in Factor Invariance Studies

Model identification in multi-group confirmatory factor analysis (MCFA) requires an equality constraint of referent variables across groups. Invariance assumption violations make it difficult to locate parameters that actually differ. Suggested procedures for locating invariant referents are cumbersome, complex, and provide imperfect results. Exploratory factor analysis (EFA) may be an alternative because of its ease of use, yet empirical evaluation of its effectiveness is lacking. EFAs accuracy for distinguishing invariant from non-invariant referents was examined

Comparing Factor Loadings in Exploratory Factor Analysis: A New Randomization Test

Factorial invariance testing requires a referent loading to be constrained equal across groups. This study introduces a randomization test for comparing group exploratory factor analysis loadings so as to identify an invariant referent. Results show that it maintains the Type I error rate while providing adequate power under most conditions

Parameter Estimation with Mixture Item Response Theory Models: A Monte Carlo Comparison of Maximum Likelihood and Bayesian Methods

The Mixture Item Response Theory (MixIRT) can be used to identify latent classes of examinees in data as well as to estimate item parameters such as difficulty and discrimination for each of the groups. Parameter estimation via maximum likelihood (MLE) and Bayesian estimation based on the Markov Chain Monte Carlo (MCMC) are compared for classification accuracy and parameter estimation bias for difficulty and discrimination. Standard error magnitude and coverage rates were compared across number of items, number of latent groups, group size ratio, total sample size and underlying item response model. Results show that MCMC provides more accurate group membership recovery across conditions and more accurate parameter estimates for smaller samples and fewer items. MLE produces narrower confidence intervals than MCMC and more accurate parameter estimates for larger samples and more items. Implications of these results for research and practice are discussed

Jamming transitions in a schematic model of suspension rheology

We study the steady-state response to applied stress in a simple scalar model of sheared colloids. Our model is based on a schematic (F2) model of the glass transition, with a memory term that depends on both stress and shear rate. For suitable parameters, we find transitions from a fluid to a nonergodic, jammed state, showing zero flow rate in an interval of applied stress. Although the jammed state is a glass, we predict that jamming transitions have an analytical structure distinct from that of the conventional mode coupling glass transition. The static jamming transition we discuss is also distinct from hydrodynamic shear thickening.Comment: 7 pages; 3 figures; improved version with added references. Accepted for publication in Europhysics Letter

Responses to supplementation by dairy cows given low pasture allowances in different seasons 2. Milk production

Two factorial experiments were designed to determine the effects of stage of lactation, and season of the year, on cow responses to supplementary feeding. These experiments were conducted over consecutive years with 128 high genetic merit multiparous Holstein-Friesian cows in early, mid and late lactation in spring, summer, autumn and winter. At each stage of lactation, and in each season of the year, cows were offered a restricted pasture allowance (25 to 35 kg dry matter (DM) per cow per day), either unsupplemented (control) or with supplement at 50 MJ metabolizable energy (ME) per cow per day in experiment 1 and 80 MJ ME per cow per day in experiment 2. The two supplements given in both years were rolled maize grain (MG) and a mixture of foods formulated to nutritionally balance the diet (BR). In experiment 2, another treatment, of a generous pasture allowance (60 to 75 kg DM per cow per day) (AP), was imposed on an additional group of early lactation cows during each season. Direct milk solids (MS) (milk fat plus milk protein) responses in experiment 1 to MG were 169, 279, 195 and 251 g MS per cow per day in spring, summer, autumn and winter, respectively, while those to BR were 107, 250, 192, 289 g MS per cow per day. In experiment 2, however, milk solids responses to both supplements during spring were slightly below the control treatment, with values similar to those in experiment 1 in summer and autumn for cows on the BR but not the MG supplement. Milk solids responses to supplementary foods were largest during seasons of the year when the quantity and quality of pasture on offer resulted in the lowest milk solids yield from unsupplemented cows. When carry-over effects of feeding MG and BR on milk solids production were detected, they were only about half the magnitude of the direct effects. Serum urea concentrations were higher in control cows than those offered MG with a similar effect for BR in all but summer in experiment 1, while serum glucose concentrations were highest in winter and lowest in summer. The most important factor influencing milk solids responses was the relative food deficit (RFD) represented by the decline in milk solids yield of the respective control groups after,changing from a generous pasture allowance to restricted allowance when the feeding treatments were imposed. Total milk solids responses (direct and carry-over) to supplements were greatest when severe food restrictions, relative to the cows' current food demand, resulted in large reductions in milk solids yield of the control groups. The RFD was the best predictor of milk solids response to supplementary foods. Therefore, it is likely that cows are most responsive to supplementary foods during or immediately after the imposition of a severe food restriction

Responses to supplementation by dairy cows given low pasture allowances in different seasons 1. Pasture intake and substitution

Two factorial experiments were designed to determine the effects of stage of lactation, and season of the year, on cow responses to supplementary feeding. These experiments were conducted over consecutive years with 128 high genetic merit multiparous Holstein-Friesian cows in early, mid and late lactation in spring, summer, autumn and winter. At each stage of lactation, and in each season of the year, cows were offered a restricted pasture allowance (25 to 35 kg dry matter (DM) per cow per day), either unsupplemented (control) or supplemented with 50 MJ metabolizable energy (ME) per cow per day in experiment 1 and 80 MJ ME per cow per day in experiment 2. Two different supplements were offered, namely, rolled maize grain (MG) and a mixture of foods (BR) formulated to nutritionally balance the diet. In experiment 2, a fourth treatment consisting solely of a generous pasture allowance (60 to 75 kg DM per cow per day, AP) was introduced. Offering MG and BR increased DM intake (DMI). At the restricted pasture allowance, increasing total ME allowance (MEA) by offering supplementary foods increased ME intake (MEI) by 0.68 (s.e. 0.047) MJ per extra MJ ME offered. This highly significant (P < 0.001) linear relationship was consistent across seasons, and did not diminish at higher MEA. In experiment 2, cows in early lactation had lower substitution rates than mid and late lactation cows irrespective of season. Substitution rate was higher when higher pasture allowance or quality of pasture on offer enabled the unsupplemented cows to achieve higher DMI from pasture than at other times of the year. These results suggest that one of the key factors determining the intake response to supplementary foods is pasture allowance. Within spring calving dairying systems, the largest increases in total DMI per kg of supplement offered is likely when offering supplements to early lactation cows grazing restricted allowances of high quality pasture

Predicting prognosis in lung cancer: Use of proliferation marker, Ki67 monoclonal antibody

An investigation was carried out to assess the prognostic significance of proliferation marker Ki67 in a group of lung cancer patients treated by surgery (limited disease). Tissue was not available for Ki67 immunostaining in inoperable group. The diagnosis is established by bronchial biopsy which does not carry enough tissue for frozen section and counting. This study is supplemented by estimating the prognostic significance of histological sub-types in the operable group and in a group of inoperable patients with extensive disease. These are usually treated by radiotherapy and/or chemotherapy. In all, 267 patients were studied including 105 treated by surgery. These patients attended King\u27s College and Brompton Hospital, UK, between 1986 and 1989. With regard to proliferation marker Ki67 done for the surgical group, only patients with Ki67 scores of less than 5% did survive significantly longer than the rest. Histology did not make any significant contribution in determining prognosis in both operable and inoperable groups. Although follow-up is limited (mean 20 months), Ki67 antibody seems promising in identifying low and high grade disease in the initial stage of lung cancer. It may prove useful for category of patients with high scores to be placed on chemotherapy/radiotherapy. Results suggest that in the case of lung tumour, proliferative activity is a better prognostic indicator than histological type