Learner-controlled e-learning has become a preferred medium for the delivery of organizational training. While e-learning offers organizations and trainees many advantages, it also comes with several potential disadvantages. The aim of this study was to explore the relative efficacy of learner- and program-controlled e-learning for content that differs in its complexity. This study also explored cognitive load as a differential mediator of the interaction between learner control and training content complexity for predicting cognitive and behavioral learning outcomes. Finally, learning goal orientation was explored as a motivational individual difference that helps learners cope with complex, learner-controlled e-learning environments. Results suggest that while there is little difference between learners in learner- and program-controlled e-learning environments for content that is relatively simple in nature, complex, learner-controlled e-learning environments are detrimental to cognitive learning relative to complex, program-controlled environments. Moreover, the results suggest that this interaction is differentially mediated by cognitive load, suggesting that complex, learner-controlled environments induce high cognitive demands onto learners which ultimately inhibit cognitive learning. Finally, learning goal orientation was identified as more facilitative individual difference in learner-controlled e-learning environments relative to program-controlled and simple training environments. Theoretical and practical implications of these findings are also discussed.

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From metaphors to mathematized models, the complexity sciences are changing the ways disciplines view their worlds, and ideas borrowed from complexity are increasingly being used to structure conversations and guide research on teaching and learning. The purpose of this corpus of research is to further those conversations and to extend complex systems ideas, theories, and modeling to curricula and to research on learning and teaching. A review of the literatures of learning and of complexity science and a discussion of the intersections between those disciplines are provided. The work reported represents an evolving model of learning qua complex system and that evolution is the result of iterative cycles of design research. One of the signatures of complex systems is the presence of scale invariance and this line of research furnishes empirical evidence of scale invariant behaviors in the activity of learners engaged in participatory simulations. The offered discussion of possible causes for these behaviors and chaotic phase transitions in human learning favors real-time optimization of decision-making as the means for producing such behaviors. Beyond theoretical development and modeling, this work includes the development of teaching activities intended to introduce pre-service mathematics and science teachers to complex systems. While some of the learning goals for this activity focused on the introduction of complex systems as a content area, we also used complex systems to frame perspectives on learning. Results of scoring rubrics and interview responses from students illustrate attributes of the proposed model of complex systems learning and also how these preservice teachers made sense of the ideas. Correlations between established theories of learning and a complex adaptive systems model of learning are established and made explicit, and a means for using complex systems ideas for designing instruction is offered. It is a fundamental assumption of this research and researcher that complex systems ideas and understandings can be appropriated from more complexity-developed disciplines and put to use modeling and building increasingly productive understandings of learning and teaching.

While polynomial-time approximation algorithms remain a dominant notion in tackling computationally hard problems, the framework of parameterized complexity has been emerging rapidly in recent years. Roughly speaking, the analytic framework of parameterized complexity attempts to grasp the difference between problems which admit O(c^k . poly(n))-time algorithms such as Vertex Cover, and problems like Dominating Set for which essentially brute-force O(n^k)-algorithms are best possible until now. Problems of the former type is said to be fixed-parameter tractable (FPT) and those of the latter type are regarded intractable. In this thesis, we investigate some problems on directed graphs and a number of constraint satisfaction problems (CSPs) from the parameterized perspective. We develop fixed-parameter algorithms for some digraph problems. In particular, we focus on the basic problem of finding a tree with certain property embedded in a given digraph. New or improved fpt-algorthms are presented for finding an out-branching with many or few leaves (Directed Maximum Leaf, Directed Minimum Leaf problems). For acyclic digraphs, Directed Maximum Leaf is shown to allow a kernel with linear number of vertices. We suggest a kernel for Directed Minimum Leaf with quadratic number of vertices. An improved fpt-algorithm for finding k-Out-Tree is presented and this algorithm is incorporated as a subroutine to obtain a better algorithm for Directed Minimum Leaf. In the second part of this thesis, we concentrate on several CSPs in which we want to maximize the number of satisfied constraints and consider parameterization "above tight lower bound" for these problems. To deal with this type of parameterization, we present a new method called SABEM using probabilistic approach and applying harmonic analysis on pseudo-boolean functions. Using SABEM we show that a number of CSPs admit polynomial kernels, thus being fixed-parameter tractable. Moreover, we suggest some problem-specific combinatorial approaches to Max-2-Sat and a wide special class of Max-Lin2, which lead to a kernel of smaller size than what can be obtained using SABEM for respective problems.

The problem of designing scheduling algorithm for multi-channel (e.g., OFDM-based) wireless downlink networks is considered, where the system has a large bandwidth and proportionally large number of users to serve. For this system, while the classical MaxWeight algorithm is known to be throughput-optimal, its buffer-overflow performance is very poor (formally, it is shown that it has zero rate function in our setting). To address this, a class of algorithms called iHLQF (iterated Heaviest matching with Longest Queues First) is proposed. The algorithms in this class are shown to be throughput-optimal for a general class of arrival/channel processes, and also rate-function optimal (i.e., exponentially small buffer overflow probability) for certain arrival/channel processes, where the channel-rates are 0 or 1 packets per timeslot. iHLQF however has higher computational complexity than MaxWeight (n⁴ vs. n² computations per timeslot respectively). To overcome this issue, a new algorithm called SSG (Server-Side Greedy) is proposed. It is shown that SSG is throughput-optimal, results in a much better per-user buffer overflow performance than the MaxWeight algorithm (positive rate function for certain arrival/channel processes), and has a computational complexity (n²) that is comparable to the MaxWeight algorithm. Thus, it provides a nice trade-off between buffer-overflow performance and computational complexity. For multi-rate channel processes, where the channels can serve multiple packets per timeslot, new Markov chain-based coupling arguments are used to derive rate-function positivity results for the SSG algorithm. Finally, an algorithm called DMEQ is proposed and shown to be rate-function optimal for certain multi-rate channel scenarios, whose definition characterizes the sufficient conditions for rate-function optimality in this regime. These results are validated by both analysis and simulations. / text

This mixed model approach research explored what are the perceived essential components of an ideal organization. The data were collected from 150 leadership development seminars from 2000 to 2006 hosted by a Fortune 500 company with participants from over 239 organizations producing 5396 responses. The qualitative primary data were unitized and statistically analyzed and synthesized to reveal significant categories and their relationships. The statistically significant categories represent the essential components of an ideal organization. The original qualitative responses manifesting the significant categories are presented in alignment with the emerging complex systems leadership perspective. / text

To help contemporary couples successfully navigate the 21st Century’s individualistic, diverse, multicultural, global, postmodern relationship environment, individual, couple, and family counselors, marriage therapists, couple therapists, family psychologists, relationship coaches, marriage educators, counselor educators, and other helping professionals need to understand and promote the positive, strengths-based, holistic, and wellbeing development of couple relationships to help them succeed and flourish in the long- term. This qualitative, narrative, visual autoethnography explores the researcher’s own experience of the culture of her 27-year long soul mate relationship with her partner through the lens of Positive and Holistic Couple Relationship Development Theory (PHRDT), its 7- phase Soul Mates Model, including encounter and dating, commitment, intimacy, building a life, shadow and adversity, renewal, and completion, resulting in the metaphorical development of the philosopher’s stone or gold of the philosophers, and its 12 positive relationship development principles. The study also explores the meanings derived from 8 alchemical pictograms associated with the Soul Mates Model’s 7 phases, which of the 12 positive principles played out in her relationship, and the effectiveness of her and her partner’s deliberate efforts at positive relationship building, as well as how these experiences may inform her teaching and practice. Based on the findings, which include the recall of fourteen years of spiritual, psychic, and visionary encounters with her partner before they met, the researcher concludes that she and her partner are not only soul mates engaged in the soul mating process, but also twin souls, linked together by an unfathomable bond that has helped them develop intimacy, remain bonded through adversity, and flourish as a couple in the long-term. Additionally, the researcher concludes that the Soul Mates Model and 8 alchemical pictograms are useful mythopoeic tools to explore the positive and holistic development of the couple relationship, that all 12 positive principles played out in her relationship, and that the process of soul mating may be taught to others with help of strategic positive, holistic, and mythopoeic interventions, yet that twin- soulship cannot be taught. She thus concludes that soul mates can be grown, yet twin souls must be born.

While the effect of auditor industry specialization is well documented in prior literature, it is unclear under what conditions or for which type of firms an auditor's industry expertise matters. I hypothesize that industry specialist auditors will provide higher quality audits in settings where the likelihood of revenue manipulation is greater. I use a firm's manipulation of revenues to measure audit quality because the revenue account is significant, requires in-depth industry specific knowledge, and is subject to frequent manipulation. The results suggest that the impact of industry specialists is concentrated among firms with complex revenue recognition standards, high growth, and low institutional monitoring. Overall, my findings highlight the importance for regulators, auditors, clients, and investors to consider the circumstances in which industry expertise improves the quality of an audit.

An essential tool in biology is the alignment of multiple sequences. Biologists use multiple sequence alignments for tasks such as predicting protein structure and function, reconstructing phylogenetic trees, and finding motifs. Constructing high-quality multiple alignments is computationally hard, both in theory and in practice, and is typically done using heuristic methods. The majority of state-of-the-art multiple alignment programs employ a form and polish strategy, where in the construction phase, an initial multiple alignment is formed by progressively merging smaller alignments, starting with single sequences. Then in a local-search phase, the resulting alignment is polished by repeatedly splitting it into smaller alignments and re-merging. This merging of alignments, the basic computational problem in the construction and local-search phases of the best multiple alignment heuristics, is called the Aligning Alignments Problem. Under the sum-of-pairs objective for scoring multiple alignments, this problem may seem to be a simple extension of two-sequence alignment. It is proven here, however, that with affine gap costs (which are recognized as necessary to get biologically-informative alignments) the problem is NP-complete when gaps are counted exactly. Interestingly, this form of multiple alignment is polynomial-time solvable when we relax the exact count, showing that exact gap counts themselves are inherently hard in multiple sequence alignment. Unlike general multiple alignment however, we show that Aligning Alignments with affine gap costs and exact counts is tractable in practice, by demonstrating an effective algorithm and a fast implementation. Our software AlignAlign is both time- and space-efficient on biological data. Computational experiments on biological data show instances derived from standard benchmark suites can be optimally aligned with surprising efficiency, and experiments on simulated data show the time and space both scale well.

Results from archaeological survey provide new insights into the origins of variation among the prehistoric Native American societies that occupied the Chickasawhatchee Swamp of southwestern Georgia. Through macroregional comparison, these insights are broadly applicable to the Eastern Woodlands societies that existed across the southeastern U.S. between A.D. 150 and 1600. Theoretical frameworks concerning landscape ecology, inter-regional exchange, and agency and structure provide the organizing structure for a multi-scalar view of change that contradicts earlier models.Within the Chickasawhatchee Swamp, survey, mapping, and excavation data present a complex regional settlement system. Within the swamp, a few large settlements were occupied for the long-term, in spite of the absence of monumental architecture. Smaller surrounding sites were periodically abandoned. At the swamp's edge, several subregions were organized around civic-ceremonial mound sites. At these edges, mound sites and surrounding subregions were abandoned simultaneously. Instead of being driven by changes in political complexity, residential mobility cycles were consistent through time and related to the region's heterogeneous landscape.Macroregional spatial data comparing mound locations through time support data from the Chickasawhatchee Swamp and confirm hypotheses relating mound construction and transitional landscapes. New data emphasize continuity in inter-regional exchange networks and contradict earlier views in which the emergence of hierarchical political structures were a transformational process that fundamentally altered Eastern Woodlands political economies. Temporal continuity and spatial variation are instead most evident.