[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-585":3,"related-585":50},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":8,"published_at":11,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":24,"tags":26,"primary_topic":8,"secondary_topics":30,"classification":31,"search_phrases":44,"slug":47,"view_count":48,"doi":8,"paper":8,"created_at":49},585,"数字素养如何降低低收入农村家庭的返贫风险:基于 2016-2022 年 CFPS 数据的实证研究","https:\u002F\u002Fwww.ebiotrade.com\u002Fnewsf\u002F2026-8\u002F20260814000054981.htm","基于中国家庭追踪调查(CFPS)2016 年至 2022 年四期面板数据,以贫困脆弱性指数衡量返贫风险,运用预期贫困脆弱性(VEP)方法,实证检验数字素养对低收入农村家庭返贫风险的影响及其内在机制。构建农村低收入家庭数字素养综合指数(数字接入、数字使用、数字创造三维 9 个指标)。研究证实了数字素养的积极防贫效应,并从构建常态化返贫预防机制、实施差异化精准的低收入群体数字素养提升策略四个维度提出政策建议。",null,"《Frontiers in Sustainable Food Systems》：How does digital literacy reduce the risk of re-impoverishment of low-income rural households: an empirical study based on CFPS data from 2016 to 2022\n\n目标：有效防止农村低收入家庭返贫是完善中国常态化扶贫支持体系的核心战略要求。数字素养（Digital Literacy）构成脆弱群体参与数字经济的关键能力。然而，现有研究未能充分验证数字素养是否以及如何缓解农村低收入家庭的返贫风险。本研究旨在通过探讨数字素养对防止家庭返贫的因果效应及其内在机制来填补这一研究空白。方法：基于中国家庭追踪调查（China Family Panel Studies, CFPS）2016年至2022年的面板数据，本文进行实证分析，系统检验数字素养对农村低收入家庭返贫风险的影响及其传导机制。结果：实证结果表明，数字素养能显著降低农村低收入家庭的返贫概率。具体而言，数字素养每增加一个标准差（Standard Deviation），家庭返贫风险降低3.1%。机制分析进一步表明，数字素养通过三个有效路径缓解返贫风险：促进非农就业（Non-agricultural Employment）、提高家庭金融可得性（Financial Accessibility）、扩大个体社会网络（Social Network）。讨论：本研究证实了数字素养的积极防贫效应。基于研究结果，从构建常态化返贫预防机制、实施差异化精准的农村低收入群体数字素养提升策略等四个维度提出针对性政策建议，以巩固脱贫成果、赋能农村可持续发展。\n\n**论文解读：数字素养对低收入农村家庭返贫风险的影响与机制——基于CFPS 2016-2022年面板数据的实证研究**\n\n**一、研究背景、问题与意义**\n\n贫困是长期困扰人类社会发展的结构性挑战。尽管中国在2020年取得了脱贫攻坚战的全面胜利，近1亿农村贫困人口实现脱贫，但绝对贫困的消除并不代表贫困问题的终结。部分已脱贫的低收入群体仍存在内生发展动力不足、抗风险能力弱等问题，返贫风险可能长期存在。现有贫困研究多基于静态收入或家庭福利特征评估“当前贫困状态”，但贫困治理的可持续性更取决于对“返贫风险”的动态预测——即家庭未来遭遇冲击时维持脱贫状态的能力。当前，数字技术深度融入农村生产生活，但数字鸿沟使得大量农村家庭难以共享数字红利，数字不平等日益突出。在基础网络设施已普遍覆盖的条件下，数字经济发展带来的不公平分配主要体现为个体数字素养（Digital Literacy）的差异。然而，现有研究未能充分验证数字素养是否及如何降低低收入农村家庭的返贫风险，且其作用机制尚不清晰。因此，本研究基于中国家庭追踪调查（CFPS）2016年至2022年四期面板数据，以贫困脆弱性指数衡量返贫风险，实证检验数字素养对低收入农村家庭返贫风险的影响及其内在机制，旨在填补这一研究空白，为巩固脱贫成果和赋能农村可持续发展提供微观证据。论文发表在《Frontiers in Sustainable Food Systems》。\n\n**二、主要关键技术与方法**\n\n本研究采用的主要关键技术方法包括：第一，运用预期贫困脆弱性（Expected Poverty Vulnerability, VEP）方法测量返贫风险，基于家庭福利服从一阶马尔可夫过程（First-order Markov Process）的假设，通过矩估计方法计算家庭未来消费或收入低于特定贫困线的概率。第二，采用熵权法（Entropy Method）从数字接入、数字使用、数字创造三个维度构建农村低收入家庭数字素养的综合指数，选取9个二级指标（如手机使用、互联网使用、移动支付等）。第三，构建双向固定效应模型（Two-way Fixed Effects Model）进行基准回归，控制家庭固定效应和年份固定效应，以消除不可观测的异质性和宏观经济冲击。第四，使用工具变量法（Instrumental Variable, IV）处理内生性问题，选取同一村庄（社区）内其他农户数字素养的均值（排除自身）作为工具变量，进行两阶段最小二乘估计。第五，采用两阶段中介模型检验机制，分别纳入非农就业、金融可得性和社会网络三个中介变量，并结合Sobel检验验证中介效应。样本来源为中国家庭追踪调查（CFPS）2016、2018、2020、2022年四期平衡面板数据，涵盖25个省份，最终样本包含3,684户农村低收入家庭，共14,736个观测值。\n\n**三、研究结果**\n\n**3.1 基准回归结果**\n\n通过逐步加入控制变量的双向固定效应模型，研究发现数字素养与低收入农村家庭返贫风险之间存在显著且稳定的负相关关系。以加入全部控制变量的结果为例，数字素养的回归系数为-0.201，在1%水平上显著。结合数字素养的标准差（0.154），计算得出数字素养每增加一个标准差，返贫风险降低约3.1个百分点（0.201×0.154），相对于样本均值34.2%的返贫风险，降幅约为9.1%。这一结果支持了假设H1：数字素养能显著降低低收入农村家庭的返贫风险。控制变量中，受教育年限、健康状况、家庭资产与返贫风险负相关，家庭规模、家庭抚养比、政府救助与返贫风险正相关，符合预期。\n\n**3.2 内生性处理**\n\n为缓解反向因果等内生性问题，研究采用同一村庄其他农户数字素养均值作为工具变量。第一阶段结果显示，该工具变量与农户自身数字素养显著正相关（系数0.631，p\u003C0.01），F统计量为158.643，远高于经验阈值，排除弱工具变量问题。第二阶段结果显示，数字素养对返贫风险的影响系数为-0.284，在1%水平上显著，进一步验证了基准结果的稳健性。\n\n**3.3 稳健性检验**\n\n研究通过四种策略进行稳健性检验：①调整贫困线标准（分别采用中位收入的40%、50%、60%）；②更换数字素养测量方法（因子分析法、等权重法）；③剔除特殊样本（直辖市、户主年龄>70岁、返贫风险极端值）；④更换计量模型（Probit边际效应模型、Tobit模型、一阶差分模型）。所有策略下数字素养的系数均显著为负，且绝对值在-0.072至-0.198之间，证实了结果的高度稳健性。\n\n**3.4 机制检验**\n\n运用两阶段中介模型，研究检验了数字素养降低返贫风险的三个路径：\n\n**（1）非农就业路径**：数字素养显著促进低收入农村家庭参与非农就业（系数0.185，p\u003C0.01），在纳入非农就业变量后，数字素养对返贫风险的系数绝对值从0.201降至0.168，且非农就业自身与返贫风险显著负相关（系数-0.086，p\u003C0.01）。Sobel检验Z值为4.62（p\u003C0.01），中介效应占比16.4%，支持假设H2a。\n\n**（2）金融可得性路径**：数字素养显著提高家庭获得正规金融机构贷款的可能性（系数0.142，p\u003C0.01），纳入金融可得性变量后，数字素养系数绝对值降至0.175，金融可得性与返贫风险显著负相关（系数-0.068，p\u003C0.01）。Sobel检验Z值为3.85（p\u003C0.01），中介效应占比12.9%，支持假设H2b。\n\n**（3）社会网络路径**：数字素养显著增强家庭社会网络（以人情礼金支出的对数衡量，系数0.324，p\u003C0.01），纳入社会网络变量后，数字素养系数绝对值降至0.172，社会网络与返贫风险显著负相关（系数-0.042，p\u003C0.01）。Sobel检验Z值为3.41（p\u003C0.01），中介效应占比10.7%，支持假设H2c。\n\n**四、讨论与结论**\n\n讨论部分总结了研究的主要结论：数字素养通过促进非农就业、提高金融可得性和扩大社会网络三个渠道有效降低返贫风险，且该效应在控制内生性后依然稳健。与已有研究相比，本研究的主要贡献在于：第一，将贫困治理研究从静态收入分析扩展至动态返贫风险测量，揭示了数字素养的前瞻性防贫效应；第二，利用2016-2022年四期面板数据克服了单期横截面数据难以控制个体异质性的局限；第三，聚焦于最易返贫的低收入农村群体，使研究对象更具针对性。研究也存在不足，如数字素养测量受数据可得性限制，未深入分析不同维度数字素养的差异化影响。\n\n研究结论部分（翻译原文结论）：利用2016-2022年CFPS的四期面板数据，本文从贫困脆弱性视角测量农户返贫风险，实证检验了数字素养对低收入农村家庭返贫风险的影响及其机制。首先，提升数字素养能显著降低低收入农村家庭的返贫风险。在控制个体异质性、年份效应并处理内生性问题后，数字素养每增加一个标准差，返贫风险降低约3.1%。这一发现与周等（Zhou D. et al., 2024）、王（Wang, 2024）的结果一致，他们发现数字素养能缩小农村家庭收入差距，且贫困家庭受益更多。其次，数字素养通过促进非农就业、提高金融可得性和扩大社会网络三个路径降低返贫风险。在非农就业渠道方面，现有研究（Zhou Z. et al., 2024；Wang et al., 2025）也得出类似结论。在金融可得性渠道方面，杨等（Yang W. et al., 2025）指出数字普惠金融的减贫效应高度依赖家庭自身的数字素养水平。在社会网络渠道方面，齐等（Qi et al., 2024）发现数字社交技能发挥最显著的减贫效应，社会资本是关键中介渠道。基于此，研究建议将数字素养提升作为巩固脱贫成果的标准措施，纳入2025年后全球减贫议程，优先普及信息检索、移动支付、线上政务服务等实用数字技能，并建立数字就业服务平台、推进数字普惠金融发展、鼓励农村电商和直播带货等新业态，同时构建多元化投资机制形成长效合力。","Frontiers in Sustainable Food Systems 2026","2026-08-14T00:00:00Z","论文",10,false,78,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},18,24,20,12,4,1,"基于CFPS大样本面板数据，实证检验数字素养对农村低收入家庭返贫风险的降低作用及机制，方法严谨，结论具有政策参考价值，但发表于国际期刊且时效性稍弱。",[25],{"name":10,"url":6},[27,28,29],"数字素养","返贫风险","CFPS Frontiers",[],{"status":32,"locked":14,"version":33,"method":34,"evidence":35},"unclassified","2026-10-22.2","rules",{"candidates":36,"agricultural_evidence":42,"reason":43},[37],{"code":38,"score":22,"supported":14,"title":39,"abstract":40,"tags":41},"I6",[],[],[27],true,"缺少足够的主题证据",[45,46],"数字素养 返贫风险 CFPS Frontiers","数字素养 返贫风险","数字素养返贫风险CFPSFrontiers-585",6,"2026-08-15T23:54:33.825714Z",{"total":48,"page":22,"page_size":48,"items":51},[52,133,200,262,341,406],{"id":53,"title":54,"url":55,"summary":56,"summary_zh":57,"content":8,"source_name":58,"source_url":55,"published_at":59,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":60,"score_detail":61,"sources":66,"tags":68,"primary_topic":73,"secondary_topics":78,"classification":79,"search_phrases":108,"slug":111,"view_count":112,"doi":113,"paper":114,"created_at":132},5581,"How Does Digital Literacy Promote Inclusive Rural Growth? Micro-Level Evidence from Income Inequality Among Farm Households","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fsu182010689","Against the backdrop of the coordinated advancement of digital village construction and the common prosperity strategy, the widespread improvement in rural households’ digital literacy is emerging as a key force in reshaping rural income distribution and enabling sustainable rural development. Whether digital dividends can equitably benefit farm households with heterogeneous endowments has a direct bearing on the inclusive growth outcomes of digital village construction and the sustainable advancement of the common prosperity goal. Using three waves of panel data from the China Family Panel Studies (CFPS) covering 2018 to 2022, this paper empirically examines the impact of digital literacy on income inequality among rural households. The findings indicate that improvements in digital literacy significantly reduce rural household income inequality, and this conclusion remains robust across a series of robustness checks. Mechanism analysis reveals that digital literacy mainly curbs the widening of rural household income gaps through two core channels: expanding social capital and alleviating credit constraints. Heterogeneity analysis shows that the inequality-reducing effect of digital literacy is more pronounced among households that depend on non-agricultural income, have lower levels of human capital, or fall into relatively lower income brackets. Further analysis demonstrates that digital literacy significantly reduces inequalities in wage income, business income, and property income across rural households, whereas its mitigating effect on transfer income inequality is not statistically significant. Meanwhile, digital literacy significantly raises the probability of upward income mobility among rural households, thereby alleviating income inequality from a dynamic perspective. On the basis of these findings, this paper proposes policy implications in several areas: building a hierarchical and categorized rural digital literacy cultivation system, fostering a virtuous cycle of digital empowerment, equal opportunity, and income convergence, and optimizing income distribution structures and dynamic mobility mechanisms, with the aim of accelerating progress toward common prosperity.","在数字乡村建设与共同富裕战略协同推进的背景下，农户数字素养的普遍提升正成为重塑乡村收入分配格局、实现乡村可持续发展的重要力量。数字红利能否公平惠及禀赋异质性农户，直接关系到数字乡村建设的包容性增长成效与共同富裕目标的可持续推进。本文利用中国家庭追踪调查（CFPS）2018—2022年三期面板数据，实证检验数字素养对农户收入不平等的影响。研究发现，数字素养的提升显著降低了农户收入不平等，这一结论在一系列稳健性检验后依然成立。机制分析表明，数字素养主要通过拓展社会资本与缓解信贷约束两条核心渠道抑制农户收入差距的扩大。异质性分析显示，数字素养的减不平等效应在依赖非农收入、人力资本水平较低或处于相对较低收入区间的农户中更为明显。进一步分析发现，数字素养显著缩小了农户工资性收入、经营性收入和财产性收入的不平等，而对转移性收入不平等的缓解作用在统计上不显著。同时，数字素养显著提高了农户收入向上流动的概率，从而从动态视角缓解了收入不平等。基于上述发现，本文从构建分层分类的农户数字素养培育体系、形成数字赋能—机会均等—收入收敛的良性循环、优化收入分配结构与动态流动机制等方面提出政策启示，以期为加快共同富裕进程提供参考。","Sustainability","2026-10-21T00:00:00Z",80,{"impact":17,"substance":62,"depth":17,"authority":63,"freshness":64,"relevant":22,"comment":65},22,13,9,"基于CFPS三期面板数据的微观实证，方法规范、结论有新意，对数字乡村与共同富裕政策有参考价值，值得进入每日精选。",[67],{"name":58,"url":55},[69,27,70,71,72],"数字乡村","共同富裕","农民收入","收入不平等",{"code":38,"slug":74,"name":75,"path":76,"parent_code":77},"digital-village","数字乡村与数据要素","\u002Ftopic\u002Fdigital-agriculture\u002Fdigital-village","I",[],{"status":80,"locked":14,"version":33,"method":34,"evidence":81},"classified",{"candidates":82,"agricultural_evidence":42},[83,89,96,103],{"code":38,"score":84,"supported":42,"title":85,"abstract":86,"tags":88},8,[],[69,87],"digital village",[69,27],{"code":90,"score":48,"supported":42,"title":91,"abstract":92,"tags":95},"G6",[],[93,94],"农户收入","rural income",[],{"code":97,"score":98,"supported":42,"title":99,"abstract":100,"tags":102},"G",3,[],[101],"rural development",[],{"code":104,"score":22,"supported":14,"title":105,"abstract":106,"tags":107},"G4",[],[],[70],[109,110],"CFPS 数字素养 农户收入","数字素养 农村收入差距","CFPS数字素养农户收入-5581",0,"10.3390\u002Fsu182010689",{"doi":113,"openalex_id":115,"authors":116,"venue":58,"cited_by_count":112,"oa_url":55,"card":125,"direction":129,"ingested_from":131},"W7223105459",[117,120,123],{"name":118,"orcid":119},"Yong Feng","https:\u002F\u002Forcid.org\u002F0000-0002-8151-8594",{"name":121,"orcid":122},"Shuokai  kai Wang","https:\u002F\u002Forcid.org\u002F0009-0002-7439-1764",{"name":124,"orcid":8},"Fangping Cao",{"tldr":126,"method":127,"finding":128,"direction":129,"opportunity":130},"基于CFPS三期面板数据，实证检验数字素养对农户收入不平等的影响。","使用CFPS 2018-2022三期面板数据，进行机制与异质性分析。","数字素养通过扩展社会资本和缓解信贷约束显著缩小农户收入差距。","数字乡村与农业信息化","可延伸研究数字素养对不同收入来源不平等的差异化机制及动态收入流动路径。","openalex","2026-10-22T11:20:47.675827Z",{"id":134,"title":135,"url":136,"summary":137,"summary_zh":8,"content":8,"source_name":138,"source_url":8,"published_at":139,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":140,"score_detail":141,"sources":145,"tags":147,"primary_topic":152,"secondary_topics":158,"classification":165,"search_phrases":187,"slug":190,"view_count":22,"doi":8,"paper":191,"created_at":199},5304,"Front. Sustain. Food Syst.:数字农业技术推广与贵州辣椒种植户极端气候适应技术采纳","https:\u002F\u002Fscienmag.com\u002Fdigital-agricultural-extension-linked-to-climate-adaptation-among-chili-farmers-in-mountainous-china","Gao H, Han H (2026) 在Frontiers in Sustainable Food Systems发表论文,以贵州辣椒种植户为研究对象,发现数字农业技术推广(DATP)对极端气候适应技术采纳呈显著正相关,通过更广泛信息渠道、信息信任和应用能力发挥作用,益处与风险预期确认起调节作用;数字信息素养较高种植户DATP效应更强(系数0.326、0.408 vs. 低素养0.084、0.133),规模化种植户效应同样更强。","Frontiers in Sustainable Food Systems(2026,Article 1914305)","2026-10-13T00:00:00Z",74,{"impact":142,"substance":143,"depth":17,"authority":63,"freshness":48,"relevant":22,"comment":144},16,21,"基于贵州辣椒种植户实证数据，揭示数字农业推广对气候适应技术采纳的调节机制，结论具体且具政策参考价值，值得入选。",[146],{"name":138,"url":136},[148,149,27,150,151],"数字农业","智慧农业","气候适应","辣椒种植",{"code":153,"slug":154,"name":155,"path":156,"parent_code":157},"B1","vegetables","蔬菜","\u002Ftopic\u002Fhorticulture\u002Fvegetables","B",[159],{"code":160,"slug":161,"name":162,"path":163,"parent_code":164},"H7","climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate","H",{"status":80,"locked":14,"version":33,"method":34,"evidence":166},{"candidates":167,"agricultural_evidence":42},[168,173,177,183],{"code":169,"score":63,"supported":42,"title":170,"abstract":171,"tags":172},"I1",[148],[148],[148,149],{"code":160,"score":20,"supported":42,"title":174,"abstract":175,"tags":176},[150],[150],[150],{"code":153,"score":178,"supported":42,"title":179,"abstract":181,"tags":182},11,[180],"辣椒",[180],[],{"code":38,"score":22,"supported":14,"title":184,"abstract":185,"tags":186},[],[],[27],[188,189],"贵州 辣椒种植户 数字农业技术推广","极端气候适应 技术采纳 数字素养","贵州辣椒种植户数字农业技术推广-5304",{"doi":8,"openalex_id":8,"authors":192,"venue":8,"cited_by_count":112,"oa_url":8,"card":193,"direction":129,"ingested_from":198},[],{"tldr":194,"method":195,"finding":196,"direction":129,"opportunity":197},"研究数字农业技术推广对贵州辣椒种植户采纳极端气候适应技术的影响。","基于贵州辣椒种植户调查数据，采用回归分析检验中介与调节效应。","数字农业技术推广显著促进适应技术采纳，信息渠道、信任与应用能力起中介作用，数字素养和规模起调节作用。","可探究数字推广服务对不同作物、不同气候区农户适应行为的差异化机制与长期效果。","agent","2026-10-19T00:07:48.767992Z",{"id":201,"title":202,"url":203,"summary":204,"summary_zh":8,"content":205,"source_name":206,"source_url":8,"published_at":207,"category":208,"cover_url":8,"hotness":13,"is_selected":14,"score":209,"score_detail":210,"sources":213,"tags":215,"primary_topic":8,"secondary_topics":218,"classification":219,"search_phrases":257,"slug":260,"view_count":112,"doi":8,"paper":8,"created_at":261},5252,"山东印发《关于大力发展智慧农业的实施意见》鲁政办字〔2026〕85号","http:\u002F\u002Fwww.daiyue.gov.cn\u002Fart\u002F2026\u002F10\u002F14\u002Fart_255813_10401578.html","山东省政府办公厅10月14日印发85号文,提出到2030年粮油作物水肥一体化应用面积达2000万亩、加力推进优势产业智慧转型、智慧赋能设施农业改造升级、智慧赋能畜牧业节本增效、智慧赋能渔业产业提档升级、培育农业人工智能产业生态等7项重点任务,打造全国智慧农业发展高地。","由农业农村部门牵头，加强与发展改革、财政、科技、工业和信息化、自然资源、畜牧兽医、大数据、气象等部门沟通配合，强化省、市、县三级协同联动，确保任务落到实处。统筹乡村振兴重大专项资金等各级相关领域财政资金推进智慧农业建设，重点支持关键技术攻关、数字农业发展县和应用场景建设。省级每年支持建设30个智慧农业应用场景。优化金融服务落实税收优惠政策，支持智慧农业科技企业和创新平台发展。推动高校、科研院所与智慧农业企业深化合作，培养精通信息技术与农业产业的复合型人才。持续推动高素质农民培育、基层农技推广队伍素质提升等项目，提升生产经营主体数字素养与技能。推进智慧农业领域从业人员职业技能培训与评价，吸引各类人才投身智慧农业发展。（省委金融办、省发展改革委、省教育厅、省科技厅、省工业和信息化厅、省财政厅、省人力资源社会保障厅、省自然资源厅、省农业农村厅、省大数据局、省畜牧局、山东金融监管局、省税务局、省气象局按职责分工负责）","岱岳区人民政府(2026-10-14)","2026-10-14T00:00:00Z","政策",75,{"impact":62,"substance":143,"depth":211,"authority":64,"freshness":48,"relevant":22,"comment":212},17,"省级智慧农业实施意见，含资金、场景数量与多部门分工等实质条款，具备政策参考价值。",[214],{"name":206,"url":203},[69,149,27,216,217],"应用场景","农业政策",[],{"status":220,"locked":14,"version":33,"method":34,"evidence":221},"needs_review",{"candidates":222,"agricultural_evidence":42,"reason":256},[223,227,233,239,245,251],{"code":169,"score":20,"supported":42,"title":224,"abstract":225,"tags":226},[149],[149],[149],{"code":228,"score":98,"supported":42,"title":229,"abstract":230,"tags":232},"C",[],[231],"畜牧",[],{"code":234,"score":98,"supported":42,"title":235,"abstract":236,"tags":238},"D",[],[237],"渔业",[],{"code":240,"score":98,"supported":42,"title":241,"abstract":242,"tags":244},"F3",[],[243],"水肥一体化",[],{"code":246,"score":98,"supported":42,"title":247,"abstract":248,"tags":250},"I2",[],[249],"农业人工智能",[],{"code":38,"score":252,"supported":14,"title":253,"abstract":254,"tags":255},2,[],[],[69,27],"多个产业证据相当，需要确认主归属",[258,259],"山东 智慧农业 实施意见","智慧农业应用场景 山东","山东智慧农业实施意见-5252","2026-10-19T00:07:31.203786Z",{"id":263,"title":264,"url":265,"summary":266,"summary_zh":267,"content":8,"source_name":268,"source_url":265,"published_at":269,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":270,"score_detail":271,"sources":274,"tags":276,"primary_topic":280,"secondary_topics":284,"classification":285,"search_phrases":306,"slug":309,"view_count":112,"doi":310,"paper":311,"created_at":340},5160,"Evaluating learner satisfaction and confidence in a precision agriculture MOOC: a cross-sectional study in Palestinian higher education","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffeduc.2026.1954745","Background Precision agriculture (PA) increasingly requires graduates who can work with sensor-based, geospatial and data-driven technologies, yet access to specialised training remains uneven in many under-resourced higher-education contexts. Although massive open online courses (MOOCs) offer a potentially scalable response to this gap, empirical evaluation of precision-agriculture MOOCs and of MOOC-based learning in Palestinian higher education more broadly remains limited, so evidence on learners' satisfaction and confidence in this specific educational context is needed. Methods This study addresses that gap through a cross-sectional, questionnaire-based evaluation of learners participating in a precision agriculture MOOC developed within the BENEFIT Erasmus+ project for Palestinian higher education; the design does not support causal inference. A questionnaire administered following learners' participation in the MOOC was completed by 62 of 69 invited learners (response rate 89.9%). The course-evaluation instrument comprised eight satisfaction items and nine confidence-related items rated on a 0-4 Likert scale; five negatively worded items were reverse-scored for composite analyses. We report descriptive statistics, one-sample tests against the scale midpoint, a paired comparison of the two composites, and correlation analysis, with Spearman's ρ as a non-parametric sensitivity check. Results Learners reported positive overall satisfaction (M = 2.74, SD = 0.57) and positive overall confidence (M = 2.54, SD = 0.40), both significantly above the scale midpoint (both p \u003C 0.001, d > 1.2). Agreement was strongest for perceived MOOC design quality (82.3%), course enjoyment (75.8%), confidence in mastering content (75.8%), and confidence in passing an examination (75.8%). Satisfaction and confidence were strongly and positively correlated [ r = 0.746, 95% CI (0.610, 0.839), p \u003C 0.001; ρ = 0.757]; because both constructs were measured concurrently by self-report within the same cross-sectional survey, this association cannot establish the direction of the relationship or a causal link between the two constructs. Satisfaction was significantly higher than confidence (mean difference = 0.20, p \u003C 0.001, dz = 0.53). A single item-perceived slide information density-did not differ significantly from the neutral midpoint ( p = 0.742), and given this non-significant result and a high proportion of neutral responses (51.6%), is presented as an area that may warrant further, exploratory review rather than a confirmed design weakness. Discussion The results suggest that a structured instructional-design approach was associated with positive learner perceptions in this agriculture MOOC, while cognitive-load management in slide design may merit further, cautious attention in future course iterations.","背景：精准农业（Precision Agriculture, PA）日益需要能够运用基于传感器、地理空间和数据驱动技术的毕业生，然而在许多资源不足的高等教育环境中，获得专业培训的机会仍然不均衡。尽管大规模开放在线课程（Massive Open Online Courses, MOOCs）为弥合这一差距提供了一种潜在的可扩展方案，但针对精准农业MOOC以及更广泛的巴勒斯坦高等教育中基于MOOC的学习的实证评估仍然有限，因此需要关于学习者在这一特定教育情境中满意度和信心的证据。方法：本研究通过对参与巴勒斯坦高等教育BENEFIT Erasmus+项目所开发的精准农业MOOC的学习者进行横断面问卷评估来填补这一空白；该设计不支持因果推断。在学习者参与MOOC后发放的问卷由69名受邀学习者中的62名完成（应答率89.9%）。课程评估工具包括八个满意度条目和九个信心相关条目，采用0-4 Likert量表评分；五个负向表述条目在综合分析时进行反向计分。我们报告描述性统计、针对量表中点的单样本检验、两个综合得分的配对比较以及相关分析，并以Spearman's ρ作为非参数敏感性检验。结果：学习者报告了积极的总体满意度（M = 2.74, SD = 0.57）和积极的总体信心（M = 2.54, SD = 0.40），两者均显著高于量表中点（均p \u003C 0.001, d > 1.2）。认同度最高的方面为感知的MOOC设计质量（82.3%）、课程愉悦感（75.8%）、掌握内容的信心（75.8%）以及通过考试的信心（75.8%）。满意度与信心呈强正相关[r = 0.746, 95% CI (0.610, 0.839), p \u003C 0.001; ρ = 0.757]；由于这两个构念是在同一横断面调查中通过自我报告同时测量的，因此该关联无法确定两者关系的方向或因果关系。满意度显著高于信心（平均差 = 0.20, p \u003C 0.001, dz = 0.53）。单个条目——感知的幻灯片信息密度——与中性中点无显著差异（p = 0.742），鉴于这一非显著结果以及较高比例的中性回答（51.6%），将其作为一个可能值得进一步","Frontiers in Education","2026-10-16T00:00:00Z",61,{"impact":84,"substance":17,"depth":272,"authority":20,"freshness":64,"relevant":22,"comment":273},14,"针对巴勒斯坦精准农业慕课的小样本横断面满意度研究，方法规范、数据透明，但样本仅62人且无因果推断，属区域性教育实证，公共影响有限，可作主题聚合素材而非每日精选头条。",[275],{"name":268,"url":265},[149,27,277,278,279],"农业慕课","巴勒斯坦","高等教育",{"code":169,"slug":281,"name":282,"path":283,"parent_code":77},"smart-agriculture","智慧农业总论","\u002Ftopic\u002Fdigital-agriculture\u002Fsmart-agriculture",[],{"status":80,"locked":14,"version":33,"method":34,"evidence":286},{"candidates":287,"agricultural_evidence":42},[288,295,302],{"code":169,"score":289,"supported":42,"title":290,"abstract":292,"tags":294},15,[291],"precision agriculture",[293,291],"精准农业",[149],{"code":296,"score":48,"supported":42,"title":297,"abstract":298,"tags":301},"I7",[],[299,300],"因果推断","causal inference",[],{"code":38,"score":22,"supported":14,"title":303,"abstract":304,"tags":305},[],[],[27],[307,308],"BENEFIT Erasmus 精准农业 MOOC","巴勒斯坦 精准农业 慕课","BENEFITErasmus精准农业MOOC-5160","10.3389\u002Ffeduc.2026.1954745",{"doi":310,"openalex_id":312,"authors":313,"venue":268,"cited_by_count":112,"oa_url":333,"card":334,"direction":339,"ingested_from":131},"W7222418765",[314,316,318,321,324,327,330],{"name":315,"orcid":8},"Walid Khalilia",{"name":317,"orcid":8},"Hazem Horoub",{"name":319,"orcid":320},"Hani Iwidat","https:\u002F\u002Forcid.org\u002F0009-0007-4824-6711",{"name":322,"orcid":323},"Faiz Abdelhafid","https:\u002F\u002Forcid.org\u002F0000-0003-4758-9142",{"name":325,"orcid":326},"Radoslav Židek","https:\u002F\u002Forcid.org\u002F0000-0003-4751-1257",{"name":328,"orcid":329},"Ľubomí­r Belej","https:\u002F\u002Forcid.org\u002F0000-0001-8523-6650",{"name":331,"orcid":332},"Zuzana Palková","https:\u002F\u002Forcid.org\u002F0000-0002-5782-8656","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Feducation\u002Farticles\u002F10.3389\u002Ffeduc.2026.1954745\u002Fpdf",{"tldr":335,"method":336,"finding":337,"direction":129,"opportunity":338},"评估巴勒斯坦高校学习者对精准农业MOOC的满意度与信心。","横断面问卷，62名学习者，8项满意度+9项信心量表，描述统计与相关分析。","满意度与信心均显著高于中点且强正相关，满意度高于信心。","可研究资源匮乏地区农业MOOC的设计优化及满意度与信心的因果机制。","智慧农业 \u002F 农业物联网","2026-10-17T23:30:16.666582Z",{"id":342,"title":343,"url":344,"summary":345,"summary_zh":8,"content":8,"source_name":346,"source_url":8,"published_at":8,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":347,"score_detail":348,"sources":350,"tags":352,"primary_topic":356,"secondary_topics":357,"classification":358,"search_phrases":394,"slug":397,"view_count":22,"doi":8,"paper":398,"created_at":405},5134,"数字乡村建设的相关问题及对策建议 涉农要素供给、农业经济新业态与数字素养","http:\u002F\u002Fwww.fbxslw.com\u002Fjjlw\u002F29025.html","针对当前涉农要素供给受限的问题,文章提出:一是发挥各级政府部门在涉农要素供给中的主导作用,形成以涉农企业、数字企业为核心的产学研协同创新机制;二是积极引导农业院校、科研机构与农业企业、农户开展技术合作;三是充分发挥大数据的要素属性,完善体现当地农业农情的大数据技术平台,充分利用遥感、云计算、地理信息等新型技术;四是加大农业物联网建设力度,以农业智能设备研发及应用为基础,加强农业大数据模型与算法的结合力度。在农业经济新业态方面,文章提出继续完善农村电商、社交平台为核心的农产品数字流通渠道,推进三次产业的数字化融合力度,提升农业生产过程与生态环境保护的相容力度。最后强调提升农业生产经营主体的数字素养,通过各类数字村务、政务或教育平台向新型职业农民提供数字培训服务。","钧创学术论文网 数字乡村建设研究 2026 年 10 月",47,{"impact":142,"substance":272,"depth":20,"authority":98,"freshness":252,"relevant":22,"comment":349},"选题切合数字乡村与农业信息化方向，但属学术论文网转载的综述性对策文章，无新数据与独家结论，信源权威性和时效性均弱，不宜进入每日精选。",[351],{"name":346,"url":344},[353,69,27,354,355],"农村电商","农业物联网","农业大数据",{"code":38,"slug":74,"name":75,"path":76,"parent_code":77},[],{"status":80,"locked":14,"version":33,"method":34,"evidence":359},{"candidates":360,"agricultural_evidence":42},[361,365,370,376,382,388],{"code":38,"score":272,"supported":42,"title":362,"abstract":363,"tags":364},[69],[355],[355,69,27],{"code":366,"score":21,"supported":42,"title":367,"abstract":368,"tags":369},"E5",[],[353],[353],{"code":371,"score":21,"supported":42,"title":372,"abstract":373,"tags":375},"I5",[],[374],"物联网",[354],{"code":377,"score":98,"supported":42,"title":378,"abstract":379,"tags":381},"G1",[],[380],"产学研",[],{"code":383,"score":98,"supported":42,"title":384,"abstract":385,"tags":387},"I3",[],[386],"遥感",[],{"code":389,"score":98,"supported":42,"title":390,"abstract":391,"tags":393},"I4",[],[392],"地理信息",[],[395,396],"数字乡村建设 涉农要素供给","农业经济新业态 数字素养","数字乡村建设涉农要素供给-5134",{"doi":8,"openalex_id":8,"authors":399,"venue":8,"cited_by_count":112,"oa_url":8,"card":400,"direction":129,"ingested_from":198},[],{"tldr":401,"method":402,"finding":403,"direction":129,"opportunity":404},"分析数字乡村建设中涉农要素供给、农业新业态与数字素养问题并提出对策。","政策分析与对策建议，涉及大数据、遥感、物联网、电商平台等。","需政府主导、产学研协同，完善大数据平台与物联网，提升农民数字素养。","可实证检验数字素养培训对农户采纳数字技术及新业态参与的影响机制。","2026-10-17T00:13:45.192454Z",{"id":407,"title":408,"url":409,"summary":410,"summary_zh":411,"content":8,"source_name":412,"source_url":409,"published_at":139,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":413,"score_detail":414,"sources":416,"tags":418,"primary_topic":421,"secondary_topics":422,"classification":423,"search_phrases":430,"slug":433,"view_count":112,"doi":434,"paper":435,"created_at":452},5015,"EDUKASI DAN PENINGKATAN SCAM AWARENESS SEBAGAI UPAYA PENCEGAHAN PENIPUAN DIGITAL PADA MASYARAKAT DESA BANJARSARI","https:\u002F\u002Fdoi.org\u002F10.33558\u002Fan-nizam.v5i2.12860","The implementation of digital village initiatives in Indonesia has increasingly expanded access to digital technology in rural communities. However, the availability of technological infrastructure is not always accompanied by adequate digital literacy and cybersecurity awareness. In Desa Banjarsari, Bekasi Regency, limited understanding of digital terminology, security notifications, and common online fraud schemes may increase residents’ vulnerability to cyber threats, including phishing, malware, and social engineering. This community service program aimed to improve residents’ digital literacy and scam awareness through practical education on digital security and the recognition of online fraud risks. The program was conducted through direct engagement with the community, interactive discussions, and demonstrations of common digital security features and fraudulent practices. The educational activities emphasized the importance of understanding English terms frequently encountered in device interfaces, security notifications, and digital applications. By connecting digital terminology with everyday technology use, the program sought to strengthen participants’ practical understanding and awareness of online security. This initiative is expected to support more informed, safe, and responsible technology use among residents of Desa Banjarsari.","印度尼西亚数字乡村倡议的实施不断扩大农村社区获取数字技术的机会。然而，技术基础设施的可用性并不总是伴随着充分的数字素养和网络安全意识。在勿加泗县Banjarsari村，居民对数字术语、安全通知和常见网络诈骗手段的理解有限，这可能增加其遭受网络威胁的脆弱性，包括网络钓鱼、恶意软件和社交工程。本社区服务项目旨在通过数字安全和识别网络诈骗风险的实践教育，提升居民的数字素养和防诈骗意识。该项目通过与社区直接互动、互动讨论以及演示常见数字安全功能和诈骗手法来开展。教育活动强调理解设备界面、安全通知和数字应用中经常出现的英语术语的重要性。通过将数字术语与日常技术使用相联系，该项目旨在加强参与者对网络安全的实际理解和意识。该倡议有望支持Banjarsari村居民更加知情、安全和负责任地使用技术。","An-Nizam",42,{"impact":84,"substance":20,"depth":13,"authority":48,"freshness":48,"relevant":22,"comment":415},"印尼乡村数字素养与反诈教育案例，属数字乡村范畴但为地方性社区服务项目，信息增量与权威性有限，不建议进入每日精选。",[417],{"name":412,"url":409},[69,27,419,420],"反诈防骗","印尼农村",{"code":38,"slug":74,"name":75,"path":76,"parent_code":77},[],{"status":80,"locked":14,"version":33,"method":34,"evidence":424},{"candidates":425,"agricultural_evidence":42},[426],{"code":38,"score":84,"supported":42,"title":427,"abstract":428,"tags":429},[],[69,87],[69,27],[431,432],"Desa Banjarsari 数字素养","印尼 数字乡村 反诈","DesaBanjarsari数字素养-5015","10.33558\u002Fan-nizam.v5i2.12860",{"doi":434,"openalex_id":436,"authors":437,"venue":412,"cited_by_count":112,"oa_url":409,"card":447,"direction":129,"ingested_from":131},"W7221782802",[438,440,443,445],{"name":439,"orcid":8},"Dzaki Maulana Aji",{"name":441,"orcid":442},"Siti Nurhidayah","https:\u002F\u002Forcid.org\u002F0000-0003-3822-861X",{"name":444,"orcid":8},"Dian Desty Widyowati",{"name":446,"orcid":8},"Ummi Khoiriyah",{"tldr":448,"method":449,"finding":450,"direction":129,"opportunity":451},"通过教育提升印尼Banjarsari村居民的数字素养与防诈骗意识，预防网络欺诈。","社区服务：直接互动、讨论和演示常见数字安全功能与诈骗手法。","数字基础设施普及未伴随足够数字素养，教育可增强居民对网络威胁的防范意识。","可研究数字素养培训对农村居民防诈骗行为的长期效果及与农业信息化的结合。","2026-10-15T23:30:42.078015Z"]