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The COVID-19 pandemic has profoundly impacted global economies and healthcare systems, revealing critical vulnerabilities in both. In response, our study introduces a groundbreaking method for the detection of SARS-CoV-2 cDNA, leveraging Luminescence resonance energy transfer (LRET) between upconversion nanoparticles (UCNPs) and gold nanoparticles (AuNPs) to achieve an unprecedented detection limit of 242 femtomolar (fM). This innovative sensing platform utilizes UCNPs conjugated with one primer and AuNPs with another, targeting the 5' and 3' ends of the SARS-CoV-2 cDNA, respectively, enabling precise differentiation of mismatched DNA sequences and significantly enhancing detection specificity. Through rigorous experimental analysis, we established a quenching efficiency range from 10.4\% to 73.6\%, with an optimal midpoint of 42\%, thereby demonstrating the superior sensitivity of our method. By comparing the quenching efficiency of mismatched DNAs to the target DNA, we identified an optimal DNA:UCNP:AuNP ratio that ensures accurate detection. Our comparative analysis with existing SARS-CoV-2 detection methods revealed that our approach not only provides a lower detection limit but also offers higher specificity and potential for rapid, on-site testing. This study demonstrates the superior sensitivity and specificity of using UCNPs and AuNPs for SARS-CoV-2 cDNA detection, offering a significant advancement in rapid, accessible diagnostic technologies. Our method, characterized by its low detection limit and high precision, represents a critical step forward in managing current and future viral outbreaks, contributing to the enhancement of global healthcare responsiveness and infectious disease control., Comment: 14 pages, 5 figs

The development and application of upconversion nanoparticles (UCNPs) have garnered significant attention due to their unique optical properties and potential uses in bioimaging, drug delivery, and solar cells. However, the hydrophobic nature of UCNPs presents challenges in their synthesis and application, particularly in aqueous environments. We provide an overview of UCNPs, their synthesis challenges, and the importance of surface modification. Furthermore, we discuss the properties of \textit{LiYF_{4}:Yb, Er, Tm} UCNPs synthesized using novel 2,2-[ethylenebis(oxy)] bisacetic acid (EBAA) method and their versatile applications. Notably, the first Dynamic Light Scattering measurement on 05/22/2022 showed a size of 11.39 nm, and after 348 days on 04/05/2023, the same batch maintained a size of 13.8 nm, indicating excellent stability and no particle agglomeration over this extended period. This remarkable stability underscores the potential of UCNPs synthesized with the EBAA method for long-term applications. Finally, we compare the EBAA method with other surface modification techniques, exploring challenges and future perspectives for the use of hydrophilic UCNPs in various applications. This review aims to emphasize the significance of the EBAA method in advancing the field of upconversion nanoparticles and broadening their potential integration into diverse applications., Comment: 21 Pages, 1 table, 13 figures

Great advances in program analysis would be enabled if it were possible to derive the function of a program from inputs to outputs (or from initial states to final states, depending on how we model program semantics). Efforts to do so have always stalled against the difficulty to derive the function of loops; the expedient solution to capture the function of loops by unrolling them an arbitrary number of iterations is clearly inadequate. In this paper, we propose a relations-based method to derive the function of a C-like program, including programs that have loops nested to an arbitrary level. To capture the semantics of loops, we use the concept of invariant relation., Comment: 32 pages

Survey researchers are increasingly turning to multimode data collection to deal with declines in survey response rates and increasing costs. An efficient approach offers the less costly modes (e.g., web) followed with a more expensive mode for a subsample of the units (e.g., households) within each primary sampling unit (PSU). We present two alternatives to this traditional design. One alternative subsamples PSUs rather than units to constrain costs. The second is a hybrid design that includes a clustered (two-stage) sample and an independent, unclustered sample. Using a simulation, we demonstrate the hybrid design has considerable advantages., Comment: 60 pages, 5 exhibits, 17 figures, 1 table

The forensic attribution of the handwriting in a digitized document to multiple scribes is a challenging problem of high dimensionality. Unique handwriting styles may be dissimilar in a blend of several factors including character size, stroke width, loops, ductus, slant angles, and cursive ligatures. Previous work on labeled data with Hidden Markov models, support vector machines, and semi-supervised recurrent neural networks have provided moderate to high success. In this study, we successfully detect hand shifts in a historical manuscript through fuzzy soft clustering in combination with linear principal component analysis. This advance demonstrates the successful deployment of unsupervised methods for writer attribution of historical documents and forensic document analysis., Comment: 26 pages in total, 5 figures and 2 tables

In a viral pandemic, a few important tests are required for successful containment of the virus and reduction in severity of the infection. Among those tests, a test for the neutralizing ability of an antibody is crucial for assessment of population immunity gained through vaccination, and to test therapeutic value of antibodies made to counter the infections. Here, we report a sensitive technique to detect the relative neutralizing strength of various antibodies against the SARS-CoV-2 virus. We used bright, photostable, background-free, fluorescent upconversion nanoparticles conjugated with SARS-CoV-2 receptor binding domain as a phantom virion. A glass bottom plate coated with angiotensin-converting enzyme 2 (ACE-2) protein imitates the target cells. When no neutralizing IgG antibody was present in the sample, the particles would bind to the ACE-2 with high affinity. In contrast, a neutralizing antibody can prevent particle attachment to the ACE-2-coated substrate. A prototype system consisting of a custom-made confocal microscope was used to quantify particle attachment to the substrate. The sensitivity of this assay can reach 4.0 ng/ml and the dynamic range is from 1.0 ng/ml to 3.2 {\mu}g/ml. This is to be compared to 19 ng/ml sensitivity of commercially available kits.

This paper will report on a pilot Virtual Reality (VR) project which repurposes an existing scenario-based VR asset for health sciences. The original scenario aims to prepare health care students for home visits by allowing them to experience a semi-linear conversation with a virtual Non-Player Character (NPC). This provides a safe, non-threatening environment for students to hone the necessary skills they will need once they begin their professional careers. The NPC's simulated emotional state and reactions are changed based on the student's choice of responses. The original scenario was written in English but the opportunity to convert it into an Italian language learning resource by changing the audio files was identified and implemented. The scenario involves learners to be recurrently selecting from a number of possible responses in order to help the virtual character with his grievances regarding his father's care package. [For the complete volume, "New Educational Landscapes: Innovative Perspectives in Language Learning and Technology," see ED596359.]

Coventry University Institution Wide Language Programme (IWLP) offers beginners language learning modules to approximately 3,000 students. Each module is taught over 11 weeks for a total of one hour and 40 minutes and two of the weeks are used for in class tests, so tutors generally agree that students need to practise their skills outside the classroom in order to pass the module. One way of doing this was to use the language learning app, Duolingo, which helps students to gradually broaden their linguistic, professional competence, and digital fluency through increased learner autonomy. How effective this approach is, however, has never been measured. The project ran from January to April 2018 and explored whether a correlation exists between regular use of the app by IWLP learners at Common European Framework of Reference (CEFR) level A1 of French, German, Italian, Portuguese, and Spanish, and achieving a high formal coursework assessment mark. The views of both learners and tutors of their experiences of using the software, and the tutor tools provided by Duolingo Schools, will also be canvassed. A virtual classroom was set up within Duolingo Schools for each participating cohort of students and they were encouraged to use the app on a regular basis. The tutor tools allowed the monitoring of how many days learners were active, how many lessons they completed, how many courses they completed, and how many points they were awarded while using Duolingo. These statistics were compared with the overall formal assessment grades on modules and further data was collected at the end of the project from a representative sample of learners (182) and tutors (ten) to establish whether the software influenced module marks. [For the complete volume, "Professional Competencies in Language Learning and Teaching," see ED595297.]

We give sufficient conditions under which a random graph with a specified degree sequence is symmetric or asymmetric. In the case of bounded degree sequences, our characterisation captures the phase transition of the symmetry of the random graphs. This phase transition coincides with that of the graph connectivity. However, when the maximum degree is a growing function as the number of vertices tends to infinity, our results suggest that these two thresholds do not coincide any more, Comment: 22 pages

We present an overview of the methodology used to build a new stereo vision solution that is suitable for System on Chip. This new solution was developed to bring computer vision capability to embedded devices that live in a power constrained environment. The solution is constructured as a hybrid between classical Stereo Vision techniques and deep learning approaches. The stereoscopic module is composed of two separate modules: one that accelerates the neural network we trained and one that accelerates the front-end part. The system is completely passive and does not require any structured light to obtain very compelling accuracy. With respect to the previous Stereo Vision solutions offered by the industries we offer a major improvement is robustness to noise. This is mainly possible due to the deep learning part of the chosen architecture. We submitted our result to Middlebury dataset challenge. It currently ranks as the best System on Chip solution. The system has been developed for low latency applications which require better than real time performance on high definition videos.

This paper reports on a study that explored five student-teachers' beliefs regarding the usability of three digital flashcard websites that can be used in a blended learning approach in English Language Teaching (ELT) classrooms. These student-teachers, who had previous teaching experience, were students on a year-long Master of Arts (MA) programme at Coventry University. Adopting a mixed-method research design, this study incorporated aspects of both surveys and case studies to explore different variables that could have an effect on the use of digital flashcards in blended learning classrooms. The websites' design features appeared to create two extreme reactions in student-teachers, suggesting it might be a significant factor in shaping their beliefs. [For the complete volume, "Flipping the Blend through MOOCs, MALL and OIL--New Directions in CALL," see ED585277.]

Recent developments in mobile technologies have increased the ways in which languages can be learnt, both within and beyond the classroom. Whereas the use of mobile technologies seems to challenge traditional knowledge and skills acquisition, research shows that foreign language study can be enriched through easy access to resources selected to suit individual interests or needs (KukulskaHulme, 2013). This chapter reports on an Italian language learning game, "ImparApp," developed with the Massachusetts Institute of Technology's (MIT) "TaleBlazer" location-based game-authoring tool. Players interact with virtual characters, objects, and data as they move around their real physical location whilst attempting to solve a time travel mystery. This chapter presents data collected through a case study of how learning a language can take place beyond the traditional classroom in new and challenging ways. The chapter summarises the way learning activities were integrated into the app and discusses how the learning challenges were designed across the scenes, episodes and settings. It also presents data collected from the 'play-test' sessions and discusses initial findings of the pilot project. [For the complete volume, "Innovative Language Teaching and Learning at University: Integrating Informal Learning into Formal Language Education," see ED585162.]

Deep neural networks have achieved state-of-the-art accuracies in a wide range of computer vision, speech recognition, and machine translation tasks. However the limits of memory bandwidth and computational power constrain the range of devices capable of deploying these modern networks. To address this problem, we propose SQuantizer, a new training method that jointly optimizes for both sparse and low-precision neural networks while maintaining high accuracy and providing a high compression rate. This approach brings sparsification and low-bit quantization into a single training pass, employing these techniques in an order demonstrated to be optimal. Our method achieves state-of-the-art accuracies using 4-bit and 2-bit precision for ResNet18, MobileNet-v2 and ResNet50, even with high degree of sparsity. The compression rates of 18x for ResNet18 and 17x for ResNet50, and 9x for MobileNet-v2 are obtained when SQuantizing both weights and activations within 1% and 2% loss in accuracy for ResNets and MobileNet-v2 respectively. An extension of these techniques to object detection also demonstrates high accuracy on YOLO-v3. Additionally, our method allows for fast single pass training, which is important for rapid prototyping and neural architecture search techniques. Finally extensive results from this simultaneous training approach allows us to draw some useful insights into the relative merits of sparsity and quantization.

We introduce hybrid pruning which combines both coarse-grained channel and fine-grained weight pruning to reduce model size, computation and power demands with no to little loss in accuracy for enabling modern networks deployment on resource-constrained devices, such as always-on security cameras and drones. Additionally, to effectively perform channel pruning, we propose a fast sensitivity test that helps us quickly identify the sensitivity of within and across layers of a network to the output accuracy for target multiplier accumulators (MACs) or accuracy tolerance. Our experiment shows significantly better results on ResNet50 on ImageNet compared to existing work, even with an additional constraint of channels be hardware-friendly number.

This paper focuses on the privacy paradigm of providing access to researchers to remotely carry out analyses on sensitive data stored behind firewalls. We address the situation where the analysis demands data from multiple physically separate databases which cannot be combined. Motivating this problem are analyses using multiple data sources that currently are only possible through extension work creating a trusted user network. We develop and demonstrate a method for accurate calculation of the multivariate normal likelihood equation, for a set of parameters given the partitioned data, which can then be maximized to obtain estimates. These estimates are achieved without sharing any data or any true intermediate statistics of the data across firewalls. We show that under a certain set of assumptions our method for estimation across these partitions achieves identical results as estimation with the full data. Privacy is maintained by adding noise at each partition. This ensures each party receives noisy statistics, such that the noise cannot be removed until the last step to obtain a single value, the true total log-likelihood. Potential applications include all methods utilizing parameter estimation through maximizing the multivariate normal likelihood equation. We give detailed algorithms, along with available software, and both a real data example and simulations estimating structural equation models (SEMs) with partitioned data.

As the employment of graduates appears among the performance indicators of institutions in higher education, universities are focussing more and more upon the development of employability related skills to enhance students' prospects in the job market. All UK universities are measured on the first jobs that their students acquire after graduation. In response to this, Coventry University implemented numerous new strategies to emphasise and stress the importance of education for employability. This chapter reports on the Institution-Wide Language Provision (IWLP) and its explicit link to the higher education employability agenda. IWLPs typically cater for students who want to study a language alongside their degree subject in addition to, or as part of, their main degree course. Uniquely, Coventry University offers language modules to undergraduate students as part of a scheme called Add+vantage. These modules are designed to embed employability into undergraduate courses, allowing students to demonstrate language skills and formal learning when entering the graduate job market. The Add+vantage modules are taught over an eleven-week semester, with the eleventh week solely dedicated to employability. A short list of references and links is included. [For the complete volume, "Employability for Languages: A Handbook," see ED566902.]

The speed of technological advance in the mobile phone, netbook and tablet markets has meant that learners increasingly have access to digital devices capable of enhancing their learning experience. This case study reports on how language learners, taking Italian as an option on the Institution Wide Languages Programme (IWLP) at Coventry University, use their digital devices to support their language learning. Foreign language educators in higher education need to be aware of the degree to which learners utilise their digital devices and what they use them for. This knowledge will allow tutors to be able to offer help and support. Learners were observed using their devices in the classroom and were asked to complete a detailed questionnaire. More detailed data was then collected from a focus group of students reflecting on the numerous ways in which they used their phones to support their language learning. The case study found that the use of digital devices to support language learning was widespread and often took place outside the classroom. It also revealed that tutors were unable to recommend appropriate apps and that learners tended to use their devices autonomously and unintegrated with their modules. Learners expressed a desire for the integration of mobile language learning resources with their existing course books and on-line learning materials. [For the complete book, "10 Years of the LLAS eLearning Symposium: Case Studies in Good Practice," see ED577046.]

We present 1.4 and 2.5 GHz Australia Telescope Compact Array (ATCA) observations of the galaxy cluster A3158 (z=0.0597) which is located within the central part of the Horologium-Reticulum Supercluster (HRS). Spectroscopic data for the central part of the HRS suggest that A3158 is in a dynamically important position within the supercluster and that it is moving toward the double cluster system A3125/A3128 which marks the centre of the HRS. A total of 110 radio galaxies are detected in a 35 arcminute radius about the cluster at 1.4 GHz, of which 30 are also detected at 2.5 GHz.We examine the source counts and compute the Radio Luminosity Function (RLF) at 1.4 GHz from the subset of 88 sources found within the fullwidth half-power area of the ATCA beam. Comparison of the source counts in the area over the background, as computed by Prandoni et al. (2001), shows some evidence of an excess of galaxies with L(1.4) GHz < 2 x 10^22 W/Hz. This result seems to indicate a star forming population and is a result similar to that found recently by Owen et al. (2005) for the merging cluster A2125. In addition we find that the radio luminosity function for early-type galaxies (E and S0) below log P(1.4) = 22.5 is lower than that found for a composite cluster environment (Ledlow & Owen, 1996) but is similar to the early-type RLF for clusters in the centre of the Shapley Super cluster (Venturi et al. 2000) which are believed to be in the latter stages of merging. This result implies that the cores of superclusters are environments where radio emission, particularly resultant from AGN, is suppressed in the later stages of merging. Thus, radio observations of clusters might be sensitive indicators of the precise merger stage of the cluster but more observational evidence is still required to establish this trend., Comment: 15 pages, 10 figures, accepted to MNRAS. High resolution versions of Figures 2 & 9 will be available online in MNRAS

Missing data is a common problem in virtually all surveys. This study focuses on variance estimation and its consequences for analysis of survey data from the National Center for Education Statistics (NCES). Methods suggested by C. Sarndal (1992), S. Kaufman (1996), and S. Shao and R. Sitter (1996) are reviewed in detail. In section 3, the bootstrap method of Shao and Sitter is applied to the Schools and Staffing Survey (SASS) 1993-94 Public School Teacher Survey component to assess the magnitude of imputation variance. This method is appealing, but requires repeated imputations, so for large scale surveys, the data files become too large. The empirical study shows, however, that using the hot deck imputation method in the 1993-94 SASS can affect the standard error seriously. However, the majority of items have very low stage 2 (hot deck) imputation rates. When the imputation rate is low, the inflation in variance is not severe. It appears feasible for NCES to compute imputation rates and document the problem with the next user's manual. (Contains 8 tables and 11 references.) (SLD)

Much of the literature on random-digit-dial (RDD) response rates focuses on the benefits and drawbacks of various screening and sampling procedures. The common assumption is that enumeration is more invasive, leading to lower response rates, but there are concerns about population coverage and self-selection with other methods. When the target population is found in a subset of households, a screen-out question may be used to eliminate ineligible households prior to employing sampling methods. Using approximately 10,000 telephone numbers from the National Household Education Survey (NHES) sampling frame, this experiment examined the impact on screening response rates of: full enumeration of all households (no screen-out) versus a screen-out question, and mailing an advance letter. An RDD sample was divided into four quarter samples: (1) screen-out and letter; (2) screen-out and no letter; (3) no screen-out and letter; and (4) no screen-out and no letter. Response rates were significantly higher in the screen-out condition. The advance mailing increased cooperation in the no screen-out condition, but not in the screen-out condition. The no screen-out condition consumed substantially more resources than a screen-out sample of the same size, but also provided more data for each completed case. Implications of this experiment for the design of future surveys are discussed. Two appendixes present the NHES field test letter and the advance letter. (Contains 7 tables, 1 exhibit, and 24 references.) (Author/SLD)

The National Household Education Survey (NHES) is a telephone survey of the noninstitutionalized civilian population of the United States that collects data on educational issues that are best explored through contact with households rather than with institutions. The NHES has been conducted in 1991, 1993, 1995, and 1996. In the 1996 NHES (NHES:96), the topical components were parent/family involvement in education and civic involvement. This working paper presents information on the unit response rates, item response rates, weighting procedures, and imputation procedures in the NHES:96. The description of the response and completion rates in the first section, "Unit Response Rates," includes data on the rates for the Screener interview, the Parent/Family Involvement/Civic Involvement interview, the Youth Civic Involvement interview, and the Adult Civic Involvement interview. The next section, "Item Response and Imputation Procedures for the NHES:96," discusses reasons for nonresponse and ways to handle missing data. Imputation of missing data was done to develop complete variables used in developing sampling weights and to enable users to compute estimates more easily. The final section, "Weighting and Standard Error Calculation Procedures for the NHES:96," describes the procedures used to produce the weights for use in estimating characteristics from the NHES:96 sample and for estimating the sampling errors of those estimates. (Contains 39 tables and 7 references.) (SLD)

The National Household Education Survey (NHES) is a data collection system of the National Center for Education Statistics that is designed to provide information on educational issues that can best be studied through contacting households rather than educational institutions. This report compares the information collected through telephone interviews by the NHES on adult education in 1991 and 1995 with that collected through the Current Population Survey (CPS) of the Bureau of the Census at 3-year intervals between 1969 and 1984 and in 1992. Included in the study were examinations of population coverage and the selection of adults for interviews, survey nonresponse, the use of proxy reports of adult education participation, and survey context. In the NHES in 1991, 60,314 households were screened, and the total number of adult interviews completed was 12,568, a figure that included 9,774 adults who participated in adult education within the preceding 12 months. In 1992, approximately 57,000 households were interviewed for the CPS, a monthly survey of households. Estimates of adult education participation provided by the CPS are substantially lower than those from the NHES. The 1984 participation estimate from the CPS was 14% and the 1992 estimate was 21%. Differences in CPS and NHES estimates range from 13 to 20%. Examination of methodological, operational, and definitional issues that might account for the differences suggest that NHES figures are more accurate, although even these figures may underestimate participation. Reasons for the discrepancies are discussed. An appendix presents adult education participation items from the surveys. (Contains 9 tables and 37 references.) (SLD)

The National Household Education Survey (NHES) is a data collection system of the National Center for Education Statistics (NCES) designed to address a wide range of education-related issues. It is a telephone survey of the noninstitutionalized civilian population. This working paper presents information on the potential for undercoverage bias in estimates from the 1995 NHES. Estimates from the 1995 NHES are subject to bias because only households with telephones were sampled. Data from the 1992 October supplement to the Current Population Survey of the U.S. Census are used to evaluate the potential size of the bias of the estimates. The focus in the report is on the statistics for two separate populations: 0- to 2-year-olds who were sampled as part of the Early Childhood Program Participation (ECPP) component and civilian adults who were sampled for the Adult Education (AE) component. The analysis of undercoverage bias shows that the coverage biases for estimates of adult characteristics are not very large, but biases for 0- to 2-year-olds are somewhat larger, yet still relatively small. The coverage bias is small even though some of the differences in characteristics for persons living in telephone and nontelephone households are large. The undercoverage bias for subgroups in the NHES may be more of a problem. In this study, the undercoverage biases for characteristics of Black and Hispanic American 0- to 2-year-olds were generally larger than for all children. For adults, these undercoverage biases were not as large as for children. Overall, however, results support the use of the telephone survey methodology. An appendix presents three tables of study data. (Contains nine references.) (SLD)

The National Household Education Survey (NHES) is a data collection system of the National Center for Education Statistics (NCES) designed to address a wide range of education-related issues. It is a telephone survey of the noninstitutionalized civilian population. In 1995, the NHES included a survey of adult education (AE). This report examines errors arising from the interviewing process in the AE components of the NHES:95. The estimates from this component, and from every survey, are subject to both sampling error and nonsampling error. In this analysis, measurement errors are estimated by reinterviewing a sample of respondents and asking them a subset of the same questions included in the original interview. Statistic produced by comparing the original and reinterviews estimate the consistency of reporting. In the NHES:95 reinterviews, discrepancies between some of the original interview questions and the reinterview questions were reconciled. Reinterviews were completed with 1,109 cases. For most survey questions, the reporting was consistent, and only a few modifications need to be considered for future surveys. However, for questions associated with barriers to AE participation, more problems were identified. The greatest discrepancies were for questions about work-related activities and personal development courses. The reconciliation of the responses to the original interview and reinterview did not give much information about response bias for the questions, but the results did generally support the use of the reinterview as an independent replication of the original interview. (Contains 9 tables, 1 exhibit, and 10 references.) (SLD)

The National Household Education Survey (NHES) is a data collection system of the National Center for Education Statistics (NCES) designed to address a wide range of education-related issues. It is a telephone survey of the noninstitutionalized civilian population. In 1995, the NHES included a survey of adult education (AE). This report deals with response bias in the AE component of the NHES. To estimate response bias for the AE, an intensive reinterview was conducted with a sample of respondents and the responses to this reinterview were compared with the original values to estimate response bias. Interviewers were not chosen from the regular pool of NHES interviewers, but were people with previous experience in less structured interviews. An interview protocol was developed for the reinterview. Of 230 cases sampled for the bias study, 206 respondents completed intensive reinterviews. The estimated bias in the overall participation rate of adults was 24%, and the bias-corrected estimate is that 64% of adults participated in AE in 1995, a figure considerably larger than the 40% reported in the NHES:95. Under-reporting may have resulted from a lack of understanding related to the less formal forms of adult education. The under-reporting of participation for work-related and personal development courses was substantial. Consistency problems were identified for items dealing with barriers to participation in adult education, but the reinterview program did not lead to new ideas to cope with inconsistent reporting (the switching problem) in the NHES:95. The intensive reinterview methodology appeared to have good potential for detecting biases, and it appears that response bias can be estimated using this methodology. (Contains 9 tables and 14 references.) (SLD)

The 1991 Survey of Recent College Graduates (RCG:91) is the sixth study in a series begun in 1976. The series provides data on the occupational and educational outcomes of recent bachelor's and master's graduates one year after graduation. The survey was conducted by Westat, Inc. in a two-stage sample involving 400 institutions of higher education and 18,000 graduates contacted by telephone. Along with estimates, reports on the RCG typically include standard errors of the estimates, indicating the nature and size of sampling error. Errors due to nonsampling error are often not included in estimated standard errors, but this report examines nonsampling errors and their impact on the estimates from the RCG:91. The major sources of nonsampling errors are nonresponse, random measurement errors, and systematic errors due to interviewers. Each source is discussed, and ways to estimate the potential consequences of nonsampling errors are explored. Nine figures, 19 tables, and 3 exhibits present statistical information. Eight appendixes contain supplemental and detailed information about the conduct of the survey. (SLD)

In the spring of 1991 the first full-scale National Household Education Survey (NHES:91) was conducted for the National Center for Education Statistics (NCES). The NHES:91 was a national random digit dial telephone survey of about 14,000 parents of 3- to 8-year-old children concerning the educational experiences of young children. A reinterview program was included to examine the impact of measurement errors on estimates of the characteristics of early educational experience. For the whole subject population, there were between under 10 days and 41 days between completion of the original interview and the reinterview. The methodology and results of this computer-assisted reinterview program are discussed, comparing responses from the original and reconciled interviews. A sample of 604 cases was selected for reinterviews. Reinterviews were completed with 534 households (a response rate of 88 percent). Reinterview results are encouraging in that most items included had small to moderate measurement errors. For the specific items with high measurement errors, potential associated problems included vague or ambiguous classifications and lack of parental knowledge about the item. One weakness was the limited scope and size of the reinterview program. Four tables present analysis data. (Contains 3 references.) (SLD)

The National Household Education Survey (NHES) was conducted for the first time in 1991 as a way to collect data on the early childhood education experiences of young children and participation in adult education. Because the NHES methodology is relatively new, field tests were necessary. A large field test of approximately 15,000 households was conducted during the fall of 1989 to examine several methodological issues. This report examines a technique that was used to increase the coverage of 14- to 21-year olds and to capture more dropouts in the sample. The effectiveness of the multiplicity sample in achieving these goals is described. The multiplicity sample results in more older youths and status dropouts, but does little to add to the sample size of younger youths and the event dropouts. The multiplicity sample is effective in reducing undercoverage bias for some statistics, but not others. Ways to improve estimation are discussed. Since the cost of screening households to find those with 14- to 21-year-old members (less than 1 in 4 households) is large relative to the cost of conducting the Household Respondent Interview, it is recommended that the multiplicity sampling approach be implemented in any future survey on dropouts. One table and six figures supplement the discussion. An appendix contains five detailed tables of field test findings. (SLD)

The National Household Education Survey (NHES) was conducted for the first time in 1991 to collect data on the early childhood education (ECE) experiences of young children and participation in adult education. Because the NHES methodology is relatively new, field tests were necessary. A large field test of approximately 15,000 households was conducted during the fall of 1989 to examine several methodological issues. This report analyzes data from the Current Population Survey to identify the extent of telephone undercoverage for 14- to 21-year-olds and 3- to 5-year-olds and bias related to undercoverage for estimates of school dropouts and ECE program participation. Methods for adjusting survey estimates to reduce this bias partially are developed and evaluated. Recommendations are given to improve sampling accuracy for both populations. For estimation of 14- to 21-year-olds in the NHES, it recommended that the mean adjusted poststratified estimator be used because it incorporates an additional smoothing over the within-cell adjusted estimator. Poststratification variables that are more closely related to household income should be considered for the NHES estimation phase, and the use of tenure in addition to or in place of some of the other poststratification variables may be useful in this respect. For estimation of 3- to 5-year-olds in the NHES, the poststratified estimator appears to perform reasonably well for the range of statistics available, and it is recommended for use with this target population. Problems concerning undercoverage bias due to households without telephones were not substantial. Fourteen tables and eight figures present field test findings. An appendix discusses the source and reliability of estimates. (SLD)